Preety Anand / Grace Chung / Letian Li / Ecehan Esra Top Robert Stuart-Smith / Tyson Hosmer
HyperCELLS | TEAM:SPORES
Architectural Association School of Architecture | DRL
HyperCELLS TEAM:SPORES
Preety Anand | Grace Chung | Letian Li | Ecehan Esra Top Robert Stuart-Smith | Tyson Hosmer
PHASE II
AADRL
Architectural Association, School of Architecture - Design Research Laboratory Proto-Design (v.4) - Behavioural Matter (V.2)
Team:Spores
Preety ANAND, Grace CHUNG, Letian LI, Ecehan Esra TOP http://teamspores.com/
Tutors
Theodore Spyropoulos, Director AADRL Robert STUART-SMITH, Course Tutor Tyson HOSMER, Technical Tutor
Phase II Book February, 2013
Copyright 2013 by Team:Spores - All rights reserved All Photos and text by Team:Spores unless otherwise noted.
HyperCELLS by
TEAM:SPORES
CONTENTS 1 _Introduction DRL Course Structure 8 Proto-Design Agenda 8 Studio Agenda 10 Team 10 Thesis Statement 13 2 _Thesis Prep Architectural Critique 16 Nonlinearity 18 Slime Mould Cybernetics 20 The Chemical Machine 23 Cybernetic Approach 24 Materiality and Design 30 Methodology and Tools 35
Architectural Critique Slime Mold Research Slime Mold Tests Slime Mold Digital Exploration BZ Reaction Diffusion Research BZ Digital Exploration Material Research Slime Mould & Cybernetics
3 _Research 48 60 76 108 124 132 148 170
4 _Phase I Prototype Materiality 188 Algorithm 194 Design of The System 200 Architectural Functions 206 Integration-Disintegration 208 5 _Chemical Machine Definition 214 Theory 216 Migration Mapping 226 Mode of Operation 238 Design and Materiality 246 Physical Simulation 284 Glossary 300 5 _Mars Prototype Why Mars? 306 Research/ Precedents 308 Fabrication 328 Deployment 332 Setup 352 Systemic Performance 382
01 INTRODUCTION
_ DRL Course Structure _Proto-Design Agenda _Studio Agenda _ Team _ Thesis Statement
01 INTRODUCTION
DRL Course Structure AADRL The AA DRL is a 16-month post-professional design programme, leading to an MArch (Architecture & Urbanism) degree. For over a decade, the AA DRL has been organised as an open-source design studio dedicated to a systematic exploration of new design tools, systems and discourses, targeting design innovations in architecture and urbanism. The AA DRL investigates and develops design skills with which to capture, control and shape a continuous flow of information across the distributed electronic networks of today’s rapidly- evolving digital design disciplines. Learning in the studio is project-based and includes the development of comprehensive, year-long design projects, supported by design workshops and seminars, applying new forms of associative logic towards the conception and materialisation of comprehensive design proposals. Design work is pursued as collective self-organised design teams within five parallel design studios, addressing an overall design research agenda through shared information-based diagrams, data, models and scripts. The collaborative structure of the AA DRL design studio enables design work, which is regularly evaluated by student design teams, tutors and invited critics, and is channelled towards the development of recursive, research-based design methodologies and comprehensive design outcomes. AA DRL studio projects begin in January each year with the formation of design teams that carry forward discoveries made in Phase I Autumn Term workshops and seminars. The final proposal is presented in January, which concludes the researc based project finalized during Phase II of the program.
Proto-Design Proto-Design invastigates digital and analogue forms of computation in the pursuit of systemic design applications that are scenario and time-based. Exploring control systems as open acts of design expe imentation, the AA DRL examines production processes as active agents in the development of pr to-design systems. The challenge is to explore systems that can articulate new forms of urban deplo ment through poly-scalar correlations. Parametric and generative modelling techniques are coupled with physical computing and analogue experiments in an attempt to create dynamic processes of feedback. New forms of spatial organisations will be explored that are not type or context dependent. The aim is to identify scenarios that challenge the identification of parameters that afford systems to evolve as ecologies of machines, material and computational regulating systems towards an architecture that is adaptive and hyper specific. This performance-driven approach aims to develop novel design proposals in response to the everyday. The iterative methodologies of the design studio will be targeted towards the investigation of new spatial, structural and material organisations, participating in contemporary discourses on computation and materialisation in the disciplines of architecture and urbanism, that challenge current, industrial, repetitive modes of production.
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
01 INTRODUCTION
Studio Agenda and Team Behavioural Matter _ Studio Agenda Behavioural Matter explores how non-linear design processes may be instrumentalised to generate a temporal architecture with a designed life cycle. We will investigate an architecture that is capable of organising and reconstituting material flows – qualitatively. The Polyvalence of Architectural Matter ‘It is only in these far-from-equilibrium conditions that the full variety of immanent topological forms appears (steady state, cyclic or chaotic attractors). It is only in this zone of intensity that difference-dri en morphogenesis comes into its own, and that matter becomes an active material agent, one which does not need form to come and impose itself from the outside.’ – Manuel Delanda, Deleuze and the Genesis of Form. 1997
Methodology We will be developing event-driven, behavioural systems that define emergent tectonics that are orchestrated through computational and material methods of self-organisation that privilege the non-linear over the indexical. Emergence will be both a tectonic and aesthetic agenda as we attempt to introduce ornamental affects, along with performance criteria as qualities intrinsic to material formation. Algorithmic processes that provide feedback between design intent and environmental performance analysed in programmes such as Ecotec and Autodesk Green Building Studio will be developed. Phase 1 Design Agenda We will develop innovative algorithmic design methodologies and material production processes directed towards solving building life cycle issues whilst producing qualitative architectural affects. Phase 1 will focus on the production of large 1:1 – 1:10 scale tectonic prototypes of integrated building systems and the design of prototypical scenarios of housing unit and common space organisations. These will be further developed in Phase 2 towards a number of prototypical architectural design proposals.
Team:Spores _ Us Team:Spores is a group of four young architects within the Design Research Lab at the Architectural Association, School of Architecture in London. Positioned within a studio that seeks to challenge the means and processes of scientific research in adopting and self-organising architectural system that employs a bottom up approach to design. This method of design employs both analogue and digital model and simulation techniques in order to rigorously explore the potential of the prototype in architectural design. Grace CHUNG - Ecehan Esra TOP - Preety ANAND - Letian LI
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
01 INTRODUCTION
Thesis Statement | HyperCELLS
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
This proposals argues for a Chemical Machine, a building system, which is conceived as a cybernetic ecology capable of regulating the micro and macro environment by chemically led communication as well as purposeful morphological regulation between parts. The proposal originates from a critique on current multi-component building systems, which are based on separately fabricated parts with unsynchronized lifecycle.This research investigates an adaptive biological system of self regulation and intercellular communication between part that prevents from systemic failure - the Physarum Polycephalum (Slime mould). These features form the base of adaptive building tectonic systems which also entail critical reevaluation of the role of the architect and their conventional attitude towards matter. To enable communication and self regulation within architectural context, the self-perpetuating and regulating chemical reaction has to be materialised to a more tangible solid matter. The components are fabricated of silicone/ hydrogel spheres prepared with Belousov Zhabotinsky chemical solution. These polymeric hydrogels give an opportunity of a direct jump from chemical computation to material actuation and allow communication as well as morphological computation. In contrast to mechanically driven automation systems and sensors that clutter building services the chemical machine proposes subtraction of all mechanic or deliberate control. Through this proposal the architects role not only resides in the spatial organisation of matter, but as a contributor in the design of inherent constituency of matter itself. The proposed Chemical Machine is sensitive to environmental conditions regarding light and carbon dioxide levels by chemically led communication between components and is capable of self-regulating these conditions by continuous feedback loops. For demonstrating the mode of operation, the Chemical Machine is situated on the extreme, yet generative environment of Mars. In this context, the Chemical Machine fulfils a technological need for offering a non-human centric mode of inhabitation, which is given by mode of operation. The function of the chemical machine is not only that of generic architecture, but also a life support for both humans and biology it harbors and also is an active contributor to the greater Mars environment.The technicalities of this thesis have been developed by inter-scientific collaboration with computer scientists, material scientists and chemical engineers “Architects are suggesting how artificial machine-driven systems around them, and are beginning to build spaces that can be constantly modified and adjusted.” 1
1
Pask, Gordon. “The architectural relevance of cybernetics.”Architechtural Design. 9. (1969): 494.
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02 THESIS PREP
_ Architectural critique _ Nonlinearity _ Slime mould cybernetics _ The Chemical Machine _Cybernetic approach _ Materiality and Design _Methodology and Tools
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Architectural Critique Architectural critique The architectural critique this thesis is departing from highlights the fact that current tectonic systems are composed of multi-component systems, which are highly specified in terms of their utilization and systemic functionality. Linear and asynchronous life- and maintenance cycle of parts and subsystems cause the failure of the system as a whole when individual components fail. The failure of one part can’t be overcome by the negotiation of other remaining parts due to the system inability to communicate and self-regulate. This current state is a result of the desire of modernism for ideal functionality and increasing sophistication in the operation of building systems. However, these overly complicated systems fail due problems in design, installation, construction, failing components and erroneous modes of operation. As some of these failures remain unnoticed as they do not affect comfort, they potentially have secondary effects on other systemic components leading to their failure as well.
Fig.1: Nagakin Capsule Tower
Fig.2: The Continuous Monument (1969)
Fig.3: The Continuous Monument (1969)
Developing a radical architectural response departing from a critique on Modernism/ current architecture was similarly pursued by the Italian architects “Superstudio”. While the critique of this thesis is more focused on technological and environmental shortcomings, the critique Superstudio expressed was more focused on social, economical and political implications of Modernism due to the historic backdrop. Superstudio was not only attacking the thoughtless and monumental reductionist steel frames and concrete blocks of the post-war period capable of erasing local cultures but also the consumer culture and architecture as an”[...] formalization of present unjust social divisions[...].”1. The image series The Continuous Monument, An Architectural Model For Total Urbanization (1969) visually expresses the critique on Modernism by depicting continuous, dimensionless and gridded Mega-structures. The exaggerated monumentality together with the universally valid grid structure expose the failure and the intellectual stasis of the modernist ideals mainly driven by reason and the limited imagination of architects. “The square block is the first and ultimate act in the history of ideas in architecture. Architecture becomes a closed, immobile object that leads nowhere but to itself and to the use of reason.”2 The continuous grid, a symbol for the technological absolutism, depicts an architectural horror scenario of standardizing the world and allowing human beings to set up anywhere. The dimensionless monument is a consequence of what happens if architecture becomes a product within a society that is being ruled by consumerism thanks to globalization. “ [...] we move towards an architecture all equally emerging from a single continuous environment: the world rendered uniform by technology, culture and all the other inevitable forms of imperialism.”3 The image series however also includes the utopian desire of a unified built environment, which “[...]claims for an egalitarian society conscripted into a totalizing monumental architecture[...].” 4 This desire needs to be considered within the political backdrop of 60’s, whereas the criticized social inequality results from capitalism. On a more general note, the mega-structure is challenging the relationship between technology and social consumption. While the unifying megastructure intentionally opposes nature, it simultaneously transforms adjacent architecture into primitive objects. It needs to be clearly communicated that these forms of critical proposals, based on images with associative meanings, were never meant to be build and were intended to be e.g. magazine contributions. Furthermore, by creating a modernist monument, Superstudio actually
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
wished-for overcoming monumental modernist structures. THE CONTINUOUS MONUMENT must be read within these terms, as an architecture that does not portray “architecture” but as an architecture loaded with critical meaning, where the language of architecture is high jacked to achieve other goals than building for the sake of building.”5 While architecture is still reductive on the bigger picture, it is increasingly becoming over-specified and thus inflexible and complicated regarding technical aspects. Similar aspects of the architectural critique include the wish to overcome specialized and repetitive work, the alienated relationship between human beings and their “natural environment”, the blind faith in technological salvation and the current state of architecture leading to the wastage of energy and destruction of resources by the consumer society. Although the political backdrop has changed, the social aspects of SUPERSTUDIO’S critique are essentially still valid today.
Fig.4: Role of Architect by Yona Friedman
Furthermore, both critiques address the architectural profession. For Superstudio, negating architecture leads to the “assassination” of the architect. The architectural critique of this thesis also questions the current role of the architect, who is preoccupied with forcefully and thoughtlessly arranging disparate building parts by following universally valid deterministic order systems dictated by the building industry. “ Architecture presents no alternative proposals since it uses instruments accurately predisposed to avoid any deviation.” 6 The building industry and the architect, who is “Accepting his role [...]”7, has led to a practice unable to critically consider architectural context, while being occupied in reproducing finite architecture based on universally valid solutions taken for granted. These globally standardized building components consequently globally dictate identical ideas of predefined lifestyles. “But such structures may be open to objection on a number of grounds; culturally they may be intractable to alteration, environmentally they may be incapable of delivering the performance for which society had hoped. [...] But the architectural profession has had little to offer beyond further variations upon massive structure, and has normally responded as if these constituted the unique and unavoidable technique of dealing with environmental problems.” 8 In Architecture of the Well- Tempered Environment Banham discusses the issue of controlled interior environment of buildings with a vast array of machinic control systems which almost renders the architecture as a carcass, an almost non-necessity in assistance of human inhabitation. Our project is also a response to the issue of buildings consisting of separate and unrelated mechanic systems, each with a singular or few functions to fulfil, all working without any orchestrated intersystemic communication. Therefore what needs to be translated into architecture are systemic models that are capable of functioning multiple tasks in autocatalytic perpetuation and parallel processing.
Fig.5: Anatomy of a dwelling , Reyner Banham
Initial response The failing performance of highly specified and uncooperative disparate parts made us look at holistic and cooperative (biological) models, which are based on a small number of chemically reactive systemic members with an underspecified functionality. These systems excel in terms of a high fault tolerance and systemic robustness, which is granted by internal chemical communication and resulting self-regulation. This thesis is thus arguing for a poly-scalar approach, which is looking at the chemical detail as well as at rules for developing specific design rules for chemically driven building systems. Unlike Superstudio, it is not the intention to propose an architectural
Fig.6: Environmental Bubble , Reyner Banham 17
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Nonlinearity horror-scenario or an utopian vision, but a technologically feasible alternative-model.
How nonlinearity is able to solve architectural limitations The organizational principles and systemic logics of non-linear dynamic systems are a valid way for overcoming the linear, highly functional and specialized modernist approach regarding building components. As architecture has never been an isolated field, therefore an inevitable shift within the architectural world needs to follow the gradually changing world of sciences.
Fig.7: Slime mould
The research on a holistic biological system concluded by engaging with Physarum Polycephalum (slime mould). The slime mould, a non-hierarchical multinuclear single cell, has been examined in its Plasmodium stage regarding its performative and purposeful systemic mechanisms, which are crucial for the survival of the organism. Being a holistic system, the forceful distinction between inert matter and regulative networks, as seen in conventional building systems, is overcome. Reflecting on Jean Piaget’s notion of structure, a whole is greater than parts, and but certainly not an aggregate of separate parts but something of a greater order, which also has the abilities to transform and self- regulate; 9 this is a fitting analogy to describe a fully integrated biological system.
Nonlinearity: The Slime mould algorithm describes behavioural probabilities The behaviour of the slime mould and its ability to survive including the communicative and regulative mechanisms are mathematically expressed with the Two Variable Oregonator model. The fact that the Physarum machine follows a mathematical logic is a clear evidence for it being a computing device. Fig.8: Slime mould cycle
Fig.9: BZ cycle
The equation describes how members of the entire “Physarum machine”, such as environmental and system-based (chemical) components, are interrelated mathematically and serve as systemic activators or inhibitors. The activator, the value u, equals the concentration of the cytoplasm at the propagating wave front. The inhibitor, the value v, is a combination of the following factors : rate of nutrient consumption, by-products of chemical chains ignited by signals on photo- and chemoreceptor and concentrations of metabolites released by the plasmodium into substrate. The values u and v are based on a time scale by the parameter €. The parameter q scales the reaction rates and f is a stoichiometric coefficient. When varying coefficients of the Oregonator model are tested alternative behavioural trajectories and physical expressions are generated as expected. Changing coefficients are to be seen as data inputs of chemical nature, which cause perturbations to the nonlinear dynamic system. Visually, the Two Variable Oregonator Model describes the trajectory of the propagating wave front and thus the morphological transformations. 10 This algorithm can also describe the autocatalytic Belousov Zhabotinsky Reaction . The Belousov-Zhabotinsky Reaction is a chemical reaction which is a causal model for complex biological systems. Despite the difference in ‘constitution and composition’11 comparative to its biological archetype the reaction successfully produces phenomenological similarities. The Belousov-Zhabotinsky reaction demonstrates behaviours that are difficult to translate into digital
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Fig.10: Cycle of BZ computation due to its complex interplay of travelling local rules that respond to a larger scale global rule within a non-hierarchical system. This reaction has proliferated in the field of material sciences where this chemical reaction is directly applied. The significance of this is the subtraction of exterior control of the material physicality, and the reaction itself is inherent in the material substance which becomes a fundamental constituent of the resultant behaviour. The mathematical model also indicates the high systemic sensitivity turning the slime mould into a statistical machine. Due to that, two identical tests can have different behavioural trajectories accompanied by probabilistic transformations, whereas long term behaviour is in general unpredictable. Due to the high sensitivity, computation of the regulatory mechanisms doesn’t even halt in the absence of data inputs, indicating the existence of inter-systemic feedback. The patterning of the BZ reaction demonstrates a system of coupled feedback loops, a machinic system that internally regulate itself to self-perpetuate, and also “prevent any one phase of the process from being carried to a catastrophic extreme.�12 In biology feedback loops are often observed in communication and internal self-regulatory processes (of cells), and occurs at indiscriminate levels of scale. The BZ reaction is comparable to many natural phenomenas such as the cAMP signalling of the cellular slime mould where the produced cAMP signal 19
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Slime Mould Cybernetics
Fig.11: Two Variable Oregonator
propagates across the field, which in time diffuses to nothing and the cyclic process perpetuates. The BZ reaction have forced chemical kinetics to think about the self-organization of chemical reaction in time and space. For mathematicians and physicists, it is an ideal example of complex behaviour of nonlinear dynamical systems : limit cycle oscillations, bistability and hysteresis.13The underlying mathematical similarity between BZ reaction and these biological examples means that the reaction can serve as a simple chemical model of the invariably more complicated biological systems. Especially experiments that would be impossible or impractical in the biological setting can often be performed with ease in the BZ reaction.14 The limited capabilities of the conventional digital mode of simulation is now beginning to be recognised, and this open the possibilities of a direct jump from chemical computation to material actuation. There has already been attempts mainly in Japan and the US to directly materialise BZ reaction behaviours into ‘self-oscillating polymer gels’, which are amorphous gels that engages in some characteristic behaviours of living organisms. “Polymeric hydrogels that exhibit autonomous, coupled chemical and mechanical oscillations are a unique example of synthetic, active soft matter.”15
Position to slime mould system and algorithm It is the intention to utilize the mathematically defined behavioural capacities of the slime mould of intracellular communication and self regulation in order to design a chemically computing system, which are describable by the Oregonator Model. The algorithm describes essential systemic regulative activities, the interdependency of systemic components and the ability to overcome systemic failures by generating alternative systemic states. All these aspects are exhibited physically by a constantly changing morphology. Essential chemically controllable regulative mechanisms equal system-based modes of information processing. The biological modes of information processing can be retraced chemically, as the BZ- Reaction and the slime mould share the same systemic logic. The Chemical Machine is not isomorphic to the slime mould or a BZ-medium and no physical correlations to the slime mould are drawn.
Slime mould Cybernetics: Communication through chemical signalling
Fig.12/13: Time lapse Slime mould/ BZ
Self-regulation and (morphological) adaption for the sake of survival rely on the cooperative communicative processes among the nuclei. The nuclei are the brains of the slime mould and are encapsulated within a protective cellular membrane, which is endowed with receptors filtering chemical environmental information. The nuclei of the slime mould communicate via chemical signals such as the hormone cAMP. A scenario, where the communicative power is apparent, is when the population of individual amoebae faces the depletion of food sources and dehydration requiring the organism to migrate for acquiring new food sources. In this case, a collective and collaborative cellular fusion is the key for survival, which is enabled by chemical signalling through cAMP, which decays after the fusion process. The chemical signalling leads to the coordinated behaviour and movement of the individual amoebae forming a large communicative multi- nuclei amoeboid cell capable of migrating. In the plasmodium stage, the regulative processes are initiated and controlled by a predefined set of chemical controllers such as chemicals, light and
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electric activity. Similarly the proposed Chemical Machine, is sensitive to changing environmental and inter-systemic chemical concentration levels, and thus entirely chemically driven.
Survival: Mechanisms for regulation and control The purpose of directed and regulative mechanisms of information processing, which are of fundamental importance in biology, are highly sensitive to disturbances and therefore enable the systemic survival through constant change and adaption. Together with the environment, the inputs, the desired outputs and the internal regulatory mechanisms the whole machine is formed. Therefore the performance of the slime mould is largely coupled to the outside world. Processes of regulation and decision-making are conducted in a strategically decentralized manner due to the absence of a (central) nervous system. The autocatalytic nature of the system and the decentralized control is responsible for the systemic stability and a key feature of dynamic systems. Within the slime mould, the regulative mechanisms of the system are expressed by changing morphologies enabled by the internal recycling of matter. Physical regulative expressions are closely connected to the oscillatory rhythms, whose generation is dependent on systemic chemical concentrations. Thus, the systemic morphology can be transformed and “controlled” by the setup and the chemical nature of the environment as mentioned above. These regulatory mechanisms include excitation waves, tree-like protoplasmic networks/ tubes and seemingly resting patterns. Excitation waves can be observed on a nutrient rich environment, whereas the slime mould distributes more “matter” in order to absorb more energy. Localized wave fragments and aggregated tree-like structures can be observed on a low-nutrient substrate, as less energy can be absorbed. Skeletal tree structures and material saving tubular connections between food sources can be observed on non-nutrient substrates. Thus the dynamic physical structure is highly task oriented. The physical regulative result is accompanied by a lot of noise evident by redundant networks which is rectified gradually and mathematically describable by Brownian motion.
Fig.14: Nuclei Slime mould
Fig.15: Chemical Communication
Feedback & Oscillation As the equation describes the whole systemic argument, it becomes clear that the aspect of feedback is not executed by an external observer, but is instead an interrelated systemic mechanism. Feedback between the innumerable nuclei, the communicating components of the system, is conducted via chemical signalling. Feedback, being a system-based chemical input has an impact on the frequency of the systemic oscillatory activity, which keeps the system away from equilibrium. Oscillation, besides being a form of inter-systemic feedback, is a method for global communication. Distinct oscillatory frequencies encoding messages are based on the nature of stimuli (chemoattractants/-repulsions), which serve as perturbations to the excitable system of the slime mould. Thus, the oscillatory rhythm can be manipulated by altering the chemical gradients of an environment. This act equals changing variables of the Oregonator-algorithm. In physical tests, the increment in frequency of oscillatory rhythm happens in the event of an attractive stimulus and decreases, if the stimulus is repulsive. Physically, the frequency of oscillation is described within the slime mould by the protoplasmic streaming. Structural changes within the
Fig.16/ 17: Chemical Controller: Light/ Electricity 21
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Slime Mould Cybernetics/ The Chemical Machine ectoplasm tube regarding the aggregation of cytoplasmic actomyosin generates a hydrostatic pressure. This eventually lead to the ectoplasmic flow ( shuttling) from one location of the cell to another and back determining the rhythm of the oscillating pattern. The structural development of protoplasmic tubes is depended on the sheer stress produced by the cytoplasmic streaming driven by rhythmic contractions. Therefore there is a constant feedback between the thickness of the tube and the intensity of flux. The higher the flux, the thicker the tubular structure. The protoplasmic tubes are formed at the areas of the highest oscillatory activity, whereas tubes are abandoned once the oscillatory activity disappears.
Information and measuring In general, external as well as internal information is of chemical nature. The systemic activity, which is physically exhibited by oscillating patterns, can be measured by electric activity. This systemic activity can be quantified and evaluated, whereas the sequence of systemic states in time equals information and can be translated into a message. Quantification enables generating a measurable common systemic language. The oscillatory activity equals the action potential of a brain, whereas the electric activity is chemically seen the oscillation of calcium ion concentrations.16 Fig.18: Oscillation
Memory and learning The occurrence of periodic events leads to anticipatory behavioural patterns, and thus memory, learning and behavioural changes are associated with a chemical change in matter. Anticipatory behaviour suggests, that information of past systemic states is stored and is accessible in the form of semi-permanent memory. A more physical interpretation of memory is the tubular connection between nodes, which are inactive structures. Abandoned white tubes are long term memory, whereas the slime mould doesn’t grow over these patterns anymore. Even the sclerotium phase can be seen as long term memory, preserving the genetic information of the system. 17
Chemical material properties and physical organization of the Physarum machine
Fig.19: Measuring electric potential
Fig.20: Anticipation
The main components of the heterogeneous mass are the ectoplasm tube, which is a gel membrane layer, enclosing an endoplasmic core, the fluid state of the protoplasm. The external elastic cellular membrane consists to one half of glycoprotein, whereas the other half has a high carbohydrate to protein ratio suggesting the existence of proteoglycans. The internal protoplasm
Fig.21: Membrane and “chemical soup�
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
can be seen as an inhomogeneous chemical soup, which is composed of the following components: cyclic AMP (cAMP), calcium, phosphate, and other hosting chemicals. Together, they form the communicational channels. Considering the issue of the whole and the parts, the whole is formed by the membrane- encapsulating single cell, whereas the parts can be seen as the 1000s of nuclei responsible for communicative processes within the “chemical soup�. As matter is seen cyclic, the underspecified functional distinction between systemic components is supported by the fact that the physical structure of the single cell is composed of different material states.
Proposal: The Chemical Machine Chemical agencies-Processor- Environment The chemically self-contained machine is comprised of the environment, chemical agencies such as the inhabitant, microorganisms, plants, environmental chemicals and the processor. It is a form of life, as it is based on intracellular communication, signalling and self-regulation. The systemic members are bound together by a dynamic chemical interdependency, which is critical for the existence of the entire Machine and its members. As all systemic members rely on mutual mechanisms of information processing and self-regulation, the distinction between the inanimate and animate world is overcome and the chemical coupling allows a more collaborative rather than oppositional or hierarchical relationship between the two distinct worlds. The rituals of inhabitation and the human lifecycle are given by the operational nature of the machine. While the processor needs the disturbances given by the chemical agencies in order to avoid the state of equilibrium, the chemical agencies need to be provided with oxygen and light in order to survive. These mutual activities of self-regulation conclude in the cooperative act of survival forming an adaptive cybernetic environmental entity. The Chemical Machine is inherently sensitive to external stimuli light and carbon dioxide. If this information deviates from predefined values, localized perturbations within the Chemical Machine take place leading to emergent circuiting ( communication) and self-regulating (computation). Considering the life-supporting goals of the Chemical Machine, equilibrium equalling systemic death is strictly to be avoided. Given by the underlying statistical mathematical model, the system is highly sensitive to external chemical disturbances and inter-systemic changing concentration ratios. The Chemical Machine, being based on the interplay of chemical agencies, does not require an observer as per second order cybernetics responsible for judging the success of regulatory mechanisms. As the previously defined chemical agencies are of equal importance and impact, the Chemical Machine is essentially a non-human centric system. The Chemical Machine is of poly-scalar nature. The design starts from the chemical scale, whereas the global scale is non-foreseeable, but is critical for communicating the sense of an ecosystem. The Chemical Machine could potentially nullify energy consumption, as no electric input is needed for the system to compute and energy is of chemical nature. Fabricating components of the Chemical Machine requires a drastically different approach demanding scientific knowledge and scientific accuracy. The development of the system requires a precise and high tech approach, whereas the operation and systemic functionality is essentially low tech. Components of the Chemical Machine such as he processors will be fabricated off site in their dehydrated state.
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The Chemical Machine Situating the project and meaning of precedents Cybernetics: From deterministic to architecture free computation In order to situate the work within the field of cybernetics, an evaluation on relevant early cybernetic experiments and theories of this Second World War technology, has been conducted. As attempted by Ashby’s “Homestat” and W. Grey Walter’s “Tortoise”, the Chemical Machine is not intending to mimic biological regulatory mechanisms mechanically or electrically. An example for a deterministic cybernetic model, which is inspired by the reflex areas in the spinal cord of any animal, is Ashby’s Homeostat. The deterministic architecture of the Homeostat is made of several electronic circuits interconnected by static wiring granting communication of fixed nature. Within this model developing memory, learning or data storage is impossible. As performative aspects seem to be missing, the emphasis is on purposeful systems of control and communication for executing specified goals. “ Indeed, one could argue that for Ashby there is no analogy: the brain, like the homeostat, is simply a material switching device, connected through sensors and effectuators with the forces of the environment.” 18 A cybernetic model displaying the context between design and systemic purpose is W. Gray Walter’s Tortoise. These simple animals were constructed of three wheels, two motors for steering and motive power, light and bump censor, an electronic circuit, two batteries and a plastic shell. Interconnecting the mechanical components produces complex and unpredictable behaviours, whereas these systems are designed to have free will, uncertainty and independence. “In Grey Walter’s model of the brain, in other words, agency is fully embodied in a material set of parts and connections. Yet what is missing from this account is the necessary emphasis on the complexity of these connections. For it is precisely this complexity of connection that makes ‘‘a handful of inert components’’ yield behaviour that is interesting in itself. “19 Considering the historic developments of cybernetic models, there has been a tendency of overcoming the fixed circuit designs and deterministic brain-like control-system , as these designs are merely able to express imitative behaviour. Another projective tendency is the development from electro-mechanical to digital to chemical machines.
Fig.22: Pask, Gordon. 1950/60. Growing and dissolving matter in Chemical Computer.
These developments including temporary and emergent circuiting has been tested within Pask’s approach to cybernetics. Thus, the Paskian Chemical Computer (1950/1960) has been an important theoretical model for analysis, even though it is working without a mathematical model and essentially is a machine without goals. However, within Pask’s Chemical Computer, important ideas on architecture free computation were expressed by an unstable and unconstrained assembly of synthetic components such as a setup of an array of vertically hanging electrodes dipped into a dish with ferrous sulphate solution. These were capable of producing organic behaviours in their self-organized interplay. When a current is passed through the electrodes and a high current density occurs, dendrite branches grow at the ends of the electrodes. The branches degenerate and dissolve, if the current reaches below a critical level. Within this open ended search process, endless material configurations are possible. As Pickering points out, this
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
architecture -free computer “[...] grew without any painstaking design, exploiting the liveliness of matter instead[...].�. 20
Computer science: Chemical Computers In recent times, chemical processors operating with the logic of the Two Variable Oregonator Model, namely the Belousov Zhabotinsky Reaction, have gained the interest of experimentally working computer scientists. This aspect is crucial, as computational mechanisms of the slime mould can be retraced chemically serving an inanimate technology. Interestingly, the development on the field of chemical computation has been supported by the aspect of systemic failures due to a fixity and multiplicity of systemic components in digital computers. Conventional hard wired computers are fragile, as damaging one component usually brings the entire system to halt. Chemical computers are self healing as their physical matter can be constantly recycled. Furthermore, Reaction-diffusion processors have a high fault tolerance and are capable of automatic reconfiguration unlike digital computers. Chemical processors based on non linear chemical reactions are capable of parallel executed computational mechanisms and error correcting. Due to these parallels, the developments in the realm of non-linear chemical computation and specifically Reaction-Diffusion Processors are beneficial beyond the field of computation. The limitations however include the 2 dimensional nature of BZ-processors or even their scale and materiality. Furthermore, the Chemical Machine needs to go beyond the mathematically analogue slime mould or BZ-processors in terms of performance.
Material sciences: Polymers
Fig.23: Communicating BZ- droplets
Fig.24: Reaction Diffusion processor
The development within the field of stimuli responsive polymers as well as BZ gels is a critical factor for this thesis. There have been attempts to materialize the BZ reaction previously, so that chemical computation becomes a base for material actuation, which exhibits behaviours of living organisms. These materials operate autonomously without external deliberate control. The behaviour of the BZ gels is however limited to volumetric fluctuations only.
The project specific cybernetic approach Computation for the sake of self-regulation The Chemical Machine is utilizing principles of Reaction Diffusion Computing and in specific the BZ-processors for computational purposes. Computation and self-regulation is based on the sequential BZ chemical reaction and mathematically follows the cyclic and Oregonator logic, which links the biological model of the slime mould to the autocatalytic chemical BZ-reaction.
Fig.25: BZ gels
The purpose of the synthetic regulatory mechanisms is essentially to serve the cooperative act of survival and specifically to regulate the oxygen, hydration and light level of the microenvironment and if applicable the macro-environment. For the inhabitants as well as the potentially incorporated biological life, the Chemical Machine provides water, air, protection from drastic climate changes, food and light for plants and microorganisms to conduct photosynthesis. The Chemical Machine is capable of computing the required light level e.g. necessary for conducting photosynthesis. The Chemical Machine is capable of regulating the oxygen level as well, which is controlled by the 25
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The cybernetic approach degree of membrane pore opening for the release of stored oxygen resulting from swelling and de-swelling sub-processors. The regulatory mechanisms are cyclic in nature and are expressed by physical material behaviours such as swelling and de-swelling of sub-processors and chemical precipitation. As the same subprocessors also illuminate by chemo-luminescence, a functionally underspecified view on matter is required. However, a highly specific chemical pre-programming of the sub-processors along with their setup equalling the architecture of the computer is essential. As already argued by Gordon Pask for his Chemical Computer, the lacking specification enables modification of “[...] their systemic interconnections as they grow in order to improve proficiency at calculation or pattern recognition.”21.
Fig.26: Walter, Grey Walter. 1949. Tortoise and light stimuli.
Communication: Chemical signalling based on reagent concentrations For the regulatory chemical mechanisms to take place communication within the chemical machine is essential. For communicative processes to take place purposefully, the system filters relevant information regarding light and Oxygen level, which are found within the inhabitant as well as in the environment.
Fig.27: Walter, Grey Walter: 1949. Bodyplan Tortoise.
As per definition, communication is the transfer of encoded data. In the case of the Chemical Machine, the propagating wave of the BZ medium is responsible for transferring a message, which is encoded by concentration profiles. The propagating wave is an inter-systemic signal causing localized excitations of interconnected sub-processor. A sub-processor is susceptible to chemical signals only if it is not in the refractory period. This process of excitation leads to emergent chemical circuiting equalling changing concentration profiles of interconnected subprocessors. The capability to send and receive inter-systemic signals helps avoiding the state of equilibrium. A cybernetic example for a synthetic system capable of responding to external signals are the Tortoises developed by W. Grey Walter. These “brains” endowed with light and bump sensors scan their environment for stimuli, whereas resulting predetermined systemic behaviour depends on reconnecting electric circuits and on flow of electricity. An architectural system capable of communicating on chemical signals has certain implications as hard wired electric circuits for signal delivery and the functional distinction between inert matter and information processing networks becomes obsolete. Transient chemical circuits among the sub-processors evolve, when the wave-front starts propagating between the sub-processors. This communication allows passing on information by influencing the concentration ratio of neighbouring sub-processor. This form of chemical signalling doesn’t require specified positions for input and output, a fixed body-plan for “transmitting” a signal or any electric input.
Fig.28: Emergent circuit in BZ- vesicles
On a more global scale, the interconnection of functionally independent Chemical Machines allows a chemically led communication among these entities. In this way, behavioural and systemic states can be passed on to neighbouring processors as information and a form of input. The information can contain indications on environmental conditions as well as conditions of the neighbouring inhabitants transmitted via material states of the synthetic system. In this way, the goal of cooperative survival results in a mode of inhabitation. Systemic activities of self-regulation are not seen on an individual but on a cooperative level. The communicative power saves the
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
array of Chemical Machines from equilibrium, as processors are constantly receiving chemical signals from neighbouring processors.
Chemical control Electronically driven systems with hard wiring strongly depend on manual and deliberate rituals performed by the observer by the means of e.g. a thermostat. A thermostat, being a temperature sensing and regulating component of a control system, is responsible for maintaining the system’s desired temperature value on a constant level by comparing it to the systems actual value. It is the only regulative component allowing manual human intervention into the regulative mechanisms of heating, cooling or air conditioning systems with the aim of saving energy. By rotating the control valve, simple physical (hydraulic) principles are activated, which regulate the hot water flow from the boiler to the heating in order to achieve the desired room temperature. During this process, the fluid enclosed in the control valve gradually heats up and expands as it is a sensory element. Due to this the corrugated pipe is compressed resulting in the valve gear being pushed downwards, which cuts off the flow of hot water to the heating and equals the valve being closed. When the room temperature gradually falls, which can be seen as a systemic disturbance and a discrepancy from the desired value, the valve gear automatically shifts upwards again allowing hot water to flow through the heating. The expanding liquid performs tasks of measuring and evaluation. This sensitive self-regulating mechanism allows for a constant room temperature, if viewed over a long period. As the goal of a thermostat is to preserve dynamic equilibrium, a critical analysis of Ross Asbhy’s “Homestat” (1948) is appropriate. The “Homeostat” was developed as a regulatory device comparable to and inspired by human body parts. Homeostasis is based on delicate biological mechanisms, which perform regulatory mechanism when slight changes in e.g. temperature or chemical states are detected. The ritual and the mechanisms are suitable as well as appropriate for a mechanically working system based on physical principles. Therefore, the thermostat is not a conceptually and technically valid regulatory device for the Chemical Machine based on the computing BZ-Medium, as it does not require an active human regulatory ritual. This is given by the systemic sensitivity and excitability in the case of changing light and oxygen levels. In this way, the Chemical Machine is based on mutual control based on activation and inhibition. A deliberate and repetitive regulative ritual also implies the desire to preserve homeostatic conditions, which are technically non-existent in a non-linear dynamic system mathematically based on the Two Variable Oregonator Model.
Fig.29: Thermostat
Black Box and a reference system As the mechanisms of self-regulation cannot be observed on the chemical scale, the system equals a black box. Despite of their inaccessibility, the physically and chemically expressed regulatory results of the inanimate Chemical Machine are crucial for the inhabitants’ survival and are an immediate sign for a successful information processing. Additionally, a reference system enabling the comparison of systemic states does not exist in the classical sense, but due to the cyclic occurrence of chemical states are cyclic the system itself serves as a reference system. Furthermore, resulting physical changes in the array of processors due to chemical mechanisms should be explicit to the naked eye.
Fig.30: Ashby, Ross. 1948. Bodyplan Homeostat. 27
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The cybernetic approach Feedback Feedback has the purpose to regulate the performance of a task in case it differs from the desired output of a goal oriented machine. The feedback within the Chemical Machine works without deliberate human intervention and is not conceptualized as a corrective input. The Chemical Machine based on the Oregonator Model is dependent on negative feedback initiated by the inhibitor. In contrast, Gordon Pask’s Chemical Computer works without a feedback loop due to the nature of chemical reactions. Thus the system is wdeliberately not responsive to external controllability and is autonomous in the true sense. Therefore it is “ [...] capable of interacting with the world independently of its designer.”22
Fig.31: Walter, Walter Grey. Brain activity: Different electric patterns in different brain compartments.
Without feedback through oscillation, being a sign for high sensitivity, the Chemical Machine would reach the state of equilibrium very soon. Given by the systemic mathematical model, feedback is an essential systemically interlinked component demanding excitability. Feedback does not serve preserving a (homeo-) static condition, which would equal static chemical concentrations. Chemical precipitations resulting from regulatory mechanisms are capable of productively disturbing the systemic chemical concentrations. Thus, a precipitate can be considered as another form of inter-systemic feedback and an input. An example for a system based on corrective feedback is Ashby’s “Homeostat”, which attempts to mimic compensatory actions of humans/ animals in order to overcome systemic differences for preserving a dynamic equilibrium. Stabilization is achieved by adaptively interconnecting systemic components of the electromagnetic circuit. In this way the “brain” and regulatory systemic actions equalling feedback are embedded within one system as an entity, which is similarly envisioned within the chemically computing machine.
Intersystemic language: pH pH is an indicator by in which the system of Belousov - zhabotinsky reagents within the subprocessors regulate the spatial volume and ultimately dimension. The fluctuation in the ph is the chemical mechanism behind the swelling and the deswelling of the actual building fabric. The hydrogels expand in alkaline environment and they contract in acidic. Hypercells is a system where the building matter emcompasses a chemical regulator that is sensitive to constantly fluctuating ambient chemical levels as well as the intended manipulation / perturbation of the chemical system. Fig.32: Oscillation of activators and inhibitors
Measuring pH Information processing and messaging techniques not necessarily need to be based on electronics, as it is just one of many ways of coding. In order to monitor, whether self-regulation is successfully taking place, measurable data gained needs to be evaluated. The specifically developed measuring concept relies on pH values can be quantified and measured in time. Purposeful studies and measurements of the cyclic brain activity and electric oscillatory patterns (wavelength and rhythm) has been conducted by the neurophysiologist W. Grey Walter. These quantitative measurements became the language of his model of the cybernetic brain. “He also
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
developed a method of measuring what is called the readiness potential in human subjects, which permits an observer to predict a subject’s response about a half to one second before the subject is aware of any intention to act.” 23 With the extensive analysis on the localized alpha activity of the brain, he contributed to the development of the radar technology for war technology.
The meaning and merit of self-regulation Data storage Data storage, on a general note, creates memory in a system and if a systemic behaviour changes due to this data storage, it can be considered learning. Considering the computational logic of the BZ-processor, data storage is based on concentrations profiles of reagents. The notion of data storage, even if it is of ephemeral nature, becomes relevant in context with the self-regulation of space and volume. This condition needs to be preserved for a longer period and is expressed by coupled material behaviours, as preserving concentration profiles is not feasible within the Chemical Machine. A physically expressed self regulatory result is to be seen as systemic memory. As memory and matter are constantly recycled, there can be nothing like permanent chemical memory. Permanent chemical memory are also not useful in context with the systemic goal of self-regulation and adaption. Within Pask’s “Chemical Computer” the idea of memory is attached to the generation of matter, which is expressed by the capability of a broken thread to repair itself by reproducing the same path. [...] Once a thread was broken it would spontaneously rebuild and reconfigure itself [...].” .24 The idea of systemic robustness as per Pask’s Chemical Computer lies in the ability to self repair and matter reconfiguration and thus in the idea of memory.
Fig.33: Pask, Gordon. 1950/60. Path regeneration is memory.
Morphological Self-regulation Morphological self-regulation is expressed by the gradual, time delayed and reversible swelling and de-swelling of sub-processors. The presence of carbon-dioxide( acidic) leads to the shrinkage of sub-processors resulting in spaces and volumes expanding. If spaces are inhabited by oxygen releasing agents such as plants, spatial volumes shrink, which is due to the expansion of sub-processors in context with alkaline pH-values. Morphological aspects of self-regulation can also influence spatial subdivisions as well as the closure or opening of passages and channels depending on the frequency and intensity of utilization by the chemical agencies. As this may lead to spaces uninhabitable by people, the non-human centric nature of the Chemical Machine becomes apparent. Morphological self-regulation, depending on material behaviour, cannot be correlated to existing building tectonic functions. By self-regulation in architecture the surface to volume ratio can be improved globally and locally, as space and volume adapt in accordance to occupancy rate. It becomes a purposeful semi-permanent form adaption to a specific environmental chemical condition or a chemically unique agency. Due to the reversibility of self-regulation, the past of a system such as the interaction with a previous user are inaccessible to current inhabitants.
Fig.34: Morphological selfregulation
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Materiality and Design Materiality and Physical organization Precedents and Research Polymers Biopolymers have smaller environmental footprint than the generic materials for construction such as concrete, steel and glass. They are an extremely versatile material, where sources for its creation can be naturally or synthetically derived and after its useful lifecycle it can be reduced to almost nothing. Some of the most recent developments in the hydrogels included the following characteristics. Light sensitivity Pressure responsiveness pH sensitivity Temperature sensitivity Polymers are approaching a phase where their inherent characteristics mimic behaviours often observed in biological contexts. These types of polymers are currently being used and considered for non-mechanical biosensors, and drug delivery systems within the living organisms. The fact that these materials are also compatible with living cells are also an opportunity to deploy them inside the inhabitants as a mode of keeping biological information and communicating the sourced data to the matter that surrounds and composes the environment which they are encased in. The envisioned material articulation of this project not only resides in the macro scale. There is the potential for materials to be designed at a molecular level in terms of their molecular organisation to ultimately effect the integrity of the material at the scale that is conceivable to the naked eye, and more familiar to the human scale. Polymers are larger substances made by joining of many small and simple subunits called monomers. Despite the simplicity of its subunits its variation in its composition gives rise to complexity, and many complex and important biological examples are a result of this. The Key factors that dictate the shape, structure and material character of a polymers: Geometry of joined atoms The sequence in which monomers join to one another The physical nature of the bonds that join neighbouring monomers
Fig 35: Heat sensitive polymer (taken at LeibnizInstitut f端r Polymerforschung Dresden e. V.)
The structural complexity of these polymers are built up by sever layers in scale and hierarchy of its structures. ( Primary structure, Secondary structure, and Tertiary structure)
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Fig 53: Different types of monomer arrangements
Fig 36: Different scales of polymer structures
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Materiality and Design Copolymers Copolymers (also known as heteropolymers) are a type of polymers that are composed of two or more different types of monomers. Also how these monomers are organised at the molecular scale influences the overall character of the material. This is also a parameter and a design opportunity. These types of polymers are comparatively versatile in comparison to polymers composed of a single type of monomers as different monomers have different characteristics, and in context to our project – a potential to fulfil different tasks. Even in a seemingly homogenous matter, the differentiation in the material’s behavioural potentials can be designated and designed accordingly.
The computing engine: BZ
Fig. 37: Walking BZ gels
The chemical design of the system is based on the mathematical model ‘the two variable Oregonator’ of the Belousov Zhabotinsky (BZ) reaction. The BZ reaction is a ‘chemical model of the oxidation of organic molecules in living cells’25, which demonstrates the metabolic processes found in nature. On the surface of the solution patterns observable in nature and variations of the Turing pattern emerges. These patterns are manifested as a result of several operations running simultaneously- reaction and diffusion. This results in a system in which the concentrations of reactants and products oscillate temporally and spatially and in which this oscillation can result in ordered patterns.26 The patterning of the BZ reaction demonstrates a system of coupled feedback loops, a machinic system that internally regulate itself to self-perpetuate, and also “prevent any one phase of the process from being carried to a catastrophic extreme.”27 These phenomena are based on perturbation of the homogenous chemical system. The BZ is a highly sensitive system which reacts to a wide range of perturbations from an intended mechanical perturbation to a dust particle in air settling on the reagent’s surface. The reaction is also responsive to a range magnitude of perturbation – and this is also a parameter for design implementation, as environmental, climatic and inhabitant based perturbations will approach our project in many different form and magnitude. The environmental implication on the BZ reaction has been simulated physically through the prototype, in order to emulate the possible material implication of the BZ encapsulated within hydrogel. The precedents of such applications are currently limited to a small size , however with the prospects of possibly larger sized implications.
Material fabrication The limited capabilities of the conventional digital mode of simulation is now beginning to be recognised, and this open the possibilities of a direct jump from chemical computation to material actuation. There has already been attempts mainly in Japan and the US to directly materialise BZ reaction behaviours into ‘self-oscillating polymer gels’, which are amorphous gels that engages in some characteristic behaviours of living organisms. “Polymeric hydrogels that exhibit autonomous, coupled chemical and mechanical oscillations are a unique example of synthetic, active soft matter.”28 Although relatively new in the field of material sciences ‘soft-matter’ is a concept which is more familiar than perceived. Since the late 1980’s and the 1990’s there have been developments of “intelligent gels” or “smart gels”29. The BZ reaction is now beginning to be adopted as a mechanism that that is not external to the AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
material but an inherent material constituent. The examples are capable of autonomous colour changes or “autonomous swelling-deswelling oscillation under non-oscillatory outer conditions.”30 Developed by the Chemical Engineering and Material Sciences department at MIT, the gel displays the oscillating chemical patterns of the BZ reaction. Department OF Material Engineering University of Tokyo (Ryo Yosida), the gel sensitive to its solvent composition exhibit reversible swelling and deswelling. The volume fluctuation also enables these gels to ‘walk’. However, Yoshida acknowledges the potential of these developments “If autonomous polymer systems resembling living organisms can be realized by using completely synthetic polymers, unprecedented biomimetic materials may be created.”31 Ultimately these developments aim at creating synthetic biology, and these developments could be the initial movements to free material actuation of all scales from Newtonian dynamics.
Why biopolymers and hydrogels? Considering the cybernetic scenario of an ecology a chemically sensitive material system based on biopolymers and hydrogels is appropriate due to their capability of being coupled to biological and chemical e.g. human metabolic processes as well as to the BZ-Reaction. These materials can undergo reversible dynamic changes in accordance to changes in living systems as well. Therefore, materiality is capable of successfully executing self-regulative aspects of the Chemical Machine and does not have a secondary role. The components of the Chemical Machine are able to receive, transmit and process chemical signals in order to be engaged in self-regulation, which turns these into chemical transducers. Furthermore, silicone hydrogel is capable of absorbing the chemical reagents fully.
Design rules and criteria of Chemical Machine The design of the Chemical Machine is very much driven by performative and self-regulative intentions and has its own design rules, which do not correspond with those of generic architecture. An architecture of self-regulation not only requires an architecture equalling its setup but also leads to a form of architecture. A completely architecture-less computation as it is seen in a BZ-medium is not feasible due to the lack of controllability. Therefore setting up the chemical machine does not rely on a lack of architectural responsibility as seen in Rachel Armstrong’s approach to “Protocell Architecture”. The fact that the chemical machine needs to fulfil environmental as well as morphological tasks suggests, that the system cannot be made of a mono-material. Even in the simplest biological control systems material groupings are necessary in order to form differentiated tissues. Coexisting tissues can have multiple tasks, as deterministic and functionality designated objects have proven to be inefficient.
Molecular scale In any form of matter the changes in external conditions are immediately responded to in the molecular scale before the material affect could be observed in the macro scale. In the context 33
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Materiality and Design / Methodology and Tools of this project’s system where the range of chemical concentrations and molecular arrangements of the material determines its performance – the awareness of the inherent material quality and being able to participate in its design is critical. It is a very different approach to the traditional design role of the architect who only designed with materials of predetermined and fixed material characteristics. However this project calls for direct participation in the inherent material capacity in correspondence to its macroscopic form and arrangement.
Design of a sub-processor
Fig.38: Molecular design scale
Each chemically independent sub-processor computes with the Oregonator logic and can be considered as the CPU of the Chemical Machine, where cycles per second describe the computational power of each component. The need to compartmentalize the computing engine of the Chemical Machine into sub-processing units is critical for sustaining the propagating wave. Digital and physical studies have shown, that spherical geometries of the components correspond most suitably with the geometrical nature of the propagating wave. Considering examinations on the productivity of sub-processors, the most successful scale of each component is 20 mm diameter. In terms of materiality, each sub-processor is made of silicone-hydrogel enabling reversibility for morphological aspects of self-regulation. As the ratio of systemic inhibitors and activators (u/v ratio), can be correlated to specific pHvalues, behavioural states are designed in accordance to pH-values. While pH-values in the acidic range cause shrinkage of the sub-processor, the sub-processor swells within the alkaline range.
Fig.39: Sub-processor
Within the Chemical Machine Prototype for Mars, there is one type of sub-processor, which is both sensitive to light and carbon-dioxide at the same time. The required chemical sensitivity of the sub-processor can be specifically pre-programmed by the choice of reagents engaging in the BZ-reaction and need to be chosen in consideration with the specific scenario and interrelated environmental necessities. Besides enabling chemical sensitivity, a even higher behavioural control can be achieved by embedding thresholds for e.g. excitability.
Array of sub-processors: Maximum neighbours The arrangement of sub-processors needs to consider inter-systemic needs for communication, wave transmission and eventually self-regulation. The arrangement logic follows the idea of maximum neighbours for ensuring that each sub-processor is capable of receiving inputs from neighbouring processors. The arrangement logic of maximum neighbours allows a non-linear and non-deterministic propagation of the wave and probability in terms of spatio-temporal distributed information processing and self-regulation.
Fig.40: Maximum neighbours
A prototypical processor For the sake of designing a prototypical processor, the minimum human scale is considered, whereas in general the proposal follows a poly-scalar approach. The scale fulfils the human need for privacy and shelter.
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Matter distribution and interlinked productivity Digital studies have shown that systemic productivity is related to the strategic distribution of matter. The communicating and self-regulative capacity of the system increases with an increasing number of independently computing sub-processor. Considering this fact, 99% of the total number of sub-processors have been designated for self-regulative tasks of the Mars environment (see calculations).
Fig.41: Matter distribution
Geometry and organization of space The fact that a spherical geometry is beneficial for each sub-processor for sustaining the propagating wave, applies to the scale of space as well. A propagating wave hitting a sharp edge dissipates. Another critical fact, which was identified on the scale of sub-processors, applies to the scale of space is the rule of maximum neighbours. Both rules have architectural implications, as the processor could spatially be composed of spherical and cellular spaces.
Fig.42: Geometry of space
Membrane/ pores/ perturbation points The sub-processors are embedded within a porous hydrogel-silicone membrane allowing the sub-processors to sense the environment and to self regulate it potentially in a controlled manner. In this way the sensing and emitting membrane allows information input and output. Furthermore, the tensile membrane enables structural integrity of the inflated processor and allows morphological self-regulation.
Constraints for design Although there are plethora of opportunities in designing with versatile material such as polymers, in consideration to the current technologies there are also inevitable constraints. The major constraints are scale, taking the polymers beyond an in vitro environment, and yet keep its chemical functions and translating the polymer behaviours to an architectural necessity. Despite these constraints they are examples of physical matter that are being developed to have the embedded intelligence that is often characteristic of biological models that can be fully synthetic and as a result designed with intent. Furthermore, the mass application of a regularly small scale and highly precisely fabricated material needs to be examined.
Fig 43: Simulating Slime Mould
Digital methodologies/ tools : Simulating Slime mould information processing In the Jeff Jones Model computation is based on chemical concentrations and the interaction between Nuclei. The mobile particles, representing the Nuclei, get attracted to environmental chemical data of the indexical grid building trails. The chemical data together with design of the particle is crucial for the states of the system (behaviour) and the regulative result expressed by the changing morphology of the organism. In order to attract other particles, individual particles temporarily deposit chemical data onto the grid, which however also breaks down chemically. The Slime mould algorithm clearly expresses, that data storage is ephemeral and chemically driven.
Fig 44/45: Information processing Slime mould (Jeff Jones Model) 35
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Methodology and Tools The messaging mechanisms are heavily dependent on the design of the systemic components such as the sensory features if the particles (nuclei), as these serve as inbuilt thresholds. The fact that the aspect of probability is considered within the algorithm clearly expresses the high sensitivity of the system, where results (systemic states) are based on alternatives. It is also striking, that the mathematical approach in the algorithm is based on trigonometry, which is used to calculate waves and vibrations and is the basic mathematical theory essential for feedback driven systems. The model is thus a very good way of simulating the systemic logic of the slime mould.32
Simulating BZ reaction/ Oregonator The BZ reaction behaviour is rich and complex to the degree where there are limitations in explaining them in the context of digital simulations. This is another facet of the BZ reaction, where despite its relative simplicity of its chemical set up, the presence of several concurrent reactions makes it a challenge in its duplication outside the chemical medium. This difficulty is partly due to travelling local reactions that is also effected by a larger global rule. This does not mean a vertical hierarchy within the system, but rather a coupling of several reactions of different orders; where the word ‘order’ takes on the definition of a disposition in relation to others of equal preference. The limited capabilities of the conventional digital mode of simulation is now beginning to be recognised, and this open the possibilities of a direct jump from chemical computation to material actuation.
Model Asai The Oregonator code written by Dr. Tetsuya ASAI from the Graduate School of Information Science and Technology, Hokkaido University (Japan) has been extensively examined in the scientific article “Analog Reaction-Diffusion Chip Imitating Belousov-Zhabotinsky Reaction with Hardware Oregonator Model” (Int. Journ. of Unconventional Computing, Vol. 1, pp. 123–147, 2005). The CA-based code deals with local cell dynamics, whereas each cell arrayed on a 2D rectangular grid represents a processor computing with the Oregonator logic. The overall behaviour of the coupled identical cells is decided by the local chemically defined connection for diffusion and distance. Each cell represents the interactions between chemical species of u [i, j] and v[i, j], whereas [i,j] defines a specific point in space. The concentration of chemical species [ui, j], [vi, j] is represented by the values of system variables in each cell in the 2D space. In totality, the propagating waves of BZ are imitated by cells on a grid, while each cell representing an Oregonator/ oscillator. 33 Fig.46: Oregonator Model (Dr. Tetsuda Asai)
Model Adamatzky The Oregonator code written by Prof Andrew Adamatzky from the International Centre of Unconventional Computation, University of West England (Bristol, UK) is very much targeted towards recording time lapse videos and image-snapshots of the propagating wavefront for imitating the Pseudopodia of the Slime mould. The propagating wave-front gets attracted to “Flakes” arranged in the chemical medium. The aim is to redraw the tubular connections between the attractors in order to imitate the slime mould logic of the shortest path, which is possible due to the mathematical analogy. 34
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Project specific purpose of the Code: Behaviours of material system The rules of interaction based on the Oregonator model are given by the two above mentioned codes in its pure form. The equation and namely the meaning of the coefficients needs to be given an architectural meaning within the self-regulative systemic performances. The aim is to develop a code for simulating the morphological and environmental processes of self-regulation on long term observations. Digitally, the material behaviour following the oscillating Oregonator logic exhibiting spatially distributed cyclic behaviours such as swelling and de-swelling are be examined. The digital realm allows to examine different behavioural trajectories of the material system by setting specific concentration ratios and reaction rates allowing behavioural control and scenario specific examinations. There are several scales of digital experiments: sub-processor, array of sub-processors and eventually spaces and a processor. These simulations can consider chemical agencies such as the inhabitant. Furthermore, the digital realm is the only way of examining spatial implications of this highly speculative proposal, which is a future projection of what is currently technically feasible.
Visual means of communication Communicating a speculative project not only demands a project specific terminology, but also specifically designed visual means of communication. In the case of Superstudio’s, the image series The Continuous Monument depict a speculative project of a technologically optimistic future in the form of collages. The character of these images is mute, calm and perfect, whereas a world where consumer goods have been eliminated is portrayed. In general however, the conventions of representation have not been challenged as cartesian perspectives and artistic abstraction have been powerfully applied for visualizing the science fiction landscape. For communicating the ideas of the Chemical Machine, projective depictions of current Metropolises are an appropriate method, as these are the prime example for the failing linearity. The intended photomontages are meant to be strongly linked to the narrative of the scenario. As mentioned before, communicating the project through a narrative is indispensible due to the speculative nature in order to explain the functionality and to justify the necessity of the proposed alternative technology. It is intentional to present this technology in opposition to the failed. Due to the poly-scalar approach, the processor are meant to be displayed as a continuous structure potentially being the only option for replacing the critiqued and failed structures.
Fig. 47: Storyboard Ceremony, Superstudio.
“From the beginning, SUPERSTUDIO built its projects using the narrative vehicle of the storyboard.”35 Another powerful form of communicating a speculative project, is by the means of storyboard and film, which has been a popular tool for SUPERSTUDIO as well. Films can express scenarios in a very communicative way, whereas static images can however express the essence of a proposal or capture specific aspects. Thus, different aspects of the cybernetic system such as regulatory mechanisms, measuring, role of systemic members and poly-scalar aspects can be done by a storyboard, which would be appropriate considering this thesis’ complexity. In this context, it is worthwhile mentioning Superstudio’s Ceremony (1973) a sequence of short scenes strikingly 37
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derides the significance of tradition and domestic ritual, illustrates how life spontaneously erupts around new found ceremonies. “[...] films can be considered as propaganda for ideas outside the typical channels of the architectural discipline.”36 Communicating the functionality, the chemical interdependency and mechanisms can be done by diagrammatic explanations. It is also intended to develop functioning physical models with working sensory features. However, as discussed figuring out the limitations of these physical models is part of the design process.
Scenario: The Chemical Machine on Mars
Fig.48: Mars
The environmental chemicals can be used for systemic reasons and are necessary for the system to run. The technology is giving back to the environment rather than exploiting it. Therefore this technology becomes a necessity for human survival. The Chemical Machine on Mars is not for enabling the generic ideas on space exploration, gathering data and gaining knowledge of Mars. The Chemical Machine is also not aiming to recreate earth-like modes of inhabitation. Therefore, the scenario is also not arguing for lab and research facilities. The greater purpose of the Chemical Machine on Mars is that of seeding and propagation of life on Mars, which needs to be seen in context with its self-regulative contribution to the greater Martian environment. It is conceived as a permanent experiment, which is led probability and uncertainty. Within the scenario, it is the intention to demonstrate how a self-regulating tectonic system could lead to a mode of inhabitation. For the first 1-2 years after deployment, the processor will only harbour microorganisms for allowing a self-led building up of a microenvironment. The first arriving 30 inhabitants will bring more, but smaller scale processors (“seeds”). These “seeds” will be deployed around the initially deployed processor as a mode of growing the colony/ settlement. Each seed is conceptualized as a microenvironment. Over the course of time an ubiquitously computing ecosystem composed of chemically interrelated processors will evolve engaging in an evolutionary process.
Utopian Scenario? Fig.49: Third City: New York of Brains
Fig.50: Sixth City: Barnum Jnr’s Magnificient and Fabulous City
Communicating an architectural proposal by the means of a scenario is a powerful tool for concepts originating from a radical architectural critique. A major part of this response is the supporting research in the currently developed Reaction-Diffusion Processors, stimuli responsive biopolymers and research into second order cybernetics. With a projective attitude of the technological status the radical anti-model does not stay a mere utopian vision, as per definitions utopian models merely identify problems to be solved in a critical way and are impossible to be constructed physically. Considering precedents, the symbol-heavy scenarios depicted in Superstudio’s TWELVE CAUTIONARY TALES FOR CHRISTMAS, (12 IDEAL CITIES, 1971) are an exaggerated and ironic form of critique. A prevalent theme is the post-apocalyptical scenario illustrating utopian ideas on technology, human behaviour and life-cycle. This aspect is e.g. apparent in New York of Brains, where the human desire to gain immortality is portrayed. As per Superstudio, a very radical and negative view on human life without free will is portrayed, which is accompanied by the desired egalitarian society without economical constraints. In the
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scenarios designed by Superstudio different ideas on information processing and communication are illustrated, whereas the inhabitant is never an equal member within the system. In this way, human beings in the Ville Mechina Habitee are controlled by technology and thus victimized by it. This thesis is however concerned with a cooperation of inanimate and animate machines by coupling their lifecycles in a productive way. Another important precedent for the spontaneous adaption of human behaviour is Superstudio’s film “Ceremony”, which derides the significance of traditional human rituals of inhabitation while suggesting their emergence around the new-found. Another similarity to this thesis is the fact that the relationship between city and human is almost of cybernetic nature and a systemic interplay between the animate and the inanimate is a critical aspect. Unlike Superstudio, the design proposal of this thesis does not plays with the comforts of Modernism such as extreme sizes enabled by industrial building materials, whereas similarly to Superstudio the proposal is not intending to conform and harmonically fit within the known.
Fig.51: Ninth City: The “Ville-machine habitee”
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Endnotes 1 Peter Lang, and William Menking. Superstudio: Life without Objects , (Skira, 2003):20. 2 Peter Lang, and William Menking. Superstudio: Life without Objects , (Skira, 2003):122. 3 Peter Lang, and William Menking. Superstudio: Life without Objects , (Skira, 2003):122. 4 Peter Lang, and William Menking. Superstudio: Life without Objects , (Skira, 2003):20. 5 Peter Lang, and William Menking. Superstudio: Life without Objects , (Skira, 2003):21. 6 Peter Lang, and William Menking. Superstudio: Life without Objects , (Skira, 2003):26. 7 Peter Lang, and William Menking. Superstudio: Life without Objects , (Skira, 2003):26. 8 Reyner Banham, Architecture of the well-tempered environment, (London: Architectural Press , 1969), 21. 9 Piaget, J. Structuralism ( London: Routledge and Kegan Paul,1971): 5. 10 Adamatzky, Andrew. Physarum machines : computers from slime mould. (New Jersey : World Scientific Publishing, 2010): 57. 11 Shanks, N. “ Modelling Biological Systems: The Belousov-Zhabotinsky Reaction” Foundations of Chemistry 3, no.1, (2001) : 44 12 Keller, E.F. Making Sense of Life : Explaining Biological Development with Models, Metaphors, and Machines (Cambridge : Harvard University Press, 2002):153 13 Tyson, J. J. “What everyone Should Know About the Belousov-Zhabotinsky Reaction” Lecture Notes in Biomathematics 100, (1994) :582 14Tyson, J. J. “What everyone Should Know About the Belousov-Zhabotinsky Reaction” Lecture Notes in Biomathematics 100, (1994) :583 15 Chen, I. et al. “Shape- and Size-dependent patterns in self-oscillating polymer gels” Soft Matter 7, no.7, (2011) : 3141 16 Adamatzky, Andrew and Jeff Jones. On Electrical Correlates of Physarum Polycephalum spatial activity: Can we see Physarum machine in the dark? Biophysical Reviews and Letters 6 (2011) 29-57. 17Saigusa, Tetsu; Tero, Atsushi; Nakagaki, Toshiyuki; Kuramoto, Yoshiki (2008). “Amoebae Anticipate Periodic Events”. Physical Review Letters 100 (1): 018101 18 John JOHNSTON, Allure of machinic life : cybernetics, artificial life and the new Al, (Cambridge, MA: MIT Press, 2008), 46. 19 John JOHNSTON, Allure of machinic life : cybernetics, artificial life and the new Al, (Cambridge, MA: MIT Press, 2008), 53.
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
20 Pickering, Andrew. The Cybernetic Brain: Sketches in Another Future. Chicago ; London : Chicago University Press, 2010, page 340. 21Haque, Usman, “The architectural relevance of Gordon Pask”. 4d Social - Interactive Design Environments. Wiley & Sons (2007): 58. 22 Cariani, Peter. “To Evolve an Ear: Epistemological Implications of Gordon Pask’s Electrochemical Devices”. Systems Research, 10(3) (1993) : 20. 23 John JOHNSTON, Allure of machinic life : cybernetics, artificial life and the new Al, (Cambridge, MA: MIT Press, 2008), 47. 24 Haque, Usman, “The architectural relevance of Gordon Pask”. 4d Social - Interactive Design Environments. Wiley & Sons (2007): 58. 25 Tyson, J. J. “What everyone Should Know About the Belousov-Zhabotinsky Reaction” Lecture Notes in Biomathematics 100, (1994) : 569 26 Whitesides, G.M. Ismagilov, R.F. “Complexity in Chemistry” Science 284 (1999): 91 27 Keller, E.F. Making Sense of Life : Explaining Biological Development with Models, Metaphors, and Machines (Cambridge : Harvard University Press, 2002):153 28 Chen, I. et al. “Shape- and Size-dependent patterns in self-oscillating polymer gels” Soft Matter 7, no.7, (2011) : 3141 29 Yoshida, R. “Self-Oscillating Gel as Novel Biomimetic Materials” Journal of Controlled Release 140, no.3, (2009) : 186 30 Yoshida, R. “Self-Oscillating Gel as Novel Biomimetic Materials” Journal of Controlled Release 140, no.3, (2009) : 187 31 Yoshida, R. “Self-Oscillating Gel as Novel Biomimetic Materials” Journal of Controlled Release 140, no.3, (2009) : 186 32 Tsuda, Soichiro and Jeff Jones. The emergence of synchronization behavior in Physarum polycephalum and its particle approximation. Biosystems. Volume 103, Issue 3, March 2011, Pages 331–341. 33 Asai, Tetsuya, Yusuke Kanazawa, Tetsuya Hirose and Yoshi. “Analog Reaction-Diffusion chip imitating Belousov-Zhabotinsky Reaction with Hardware Oregonator Model.” International Journal of Unconventional Computing. Vol.1, (2005): 123-147. 34 Adamatzky, Andrew. Physarum machines : computers from slime mould. (New Jersey : World Scientific Publishing, 2010): 53-63. 35 Peter Lang, and William Menking. Superstudio: Life without Objects , (Skira, 2003):45. 36 Peter Lang, and William Menking. Superstudio: Life without Objects , (Skira, 2003):176.
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Image Credits _ Bibliography Fig.1: http://en.wikipedia.org/wiki/File:Nakagin_Capsule_Tower_2007-02-26.jpg Fig.2:http://a2d-architecture.com/post/23281644815/folly-continuous-monument-bysuperstudio-1969 Fig.3: http://www.megastructure-reloaded.org/superstudio/ Fig.4: Friedman, Yona. Towards a scientific architecture, page 5. Fig.5: http://ryanpanos.tumblr.com/post/12206167322/a-home-is-not-a-house-by-reynerbanham-and Fig. 6: http://inbetweennoise.blogspot.co.uk/2008/01/environment-bubble.html Fig.9: Whitesides, G.M. Ismagilov, R.F. “Complexity in Chemistry” Science 284 (1999): 89 Fig.11: Adamatzky, Andrew. Physarum machines : computers from slime mould. p.56. Fig.12: http://www.youtube.com/watch?v=l6kyE_cct-0 (images extracted from video) Fig. 13: Adamatzky, Andrew, Ben De Lacy Costello and Tetsuya Asai. Reaction-diffusion computers. Amsterdam ; Oxford : Elsevier, 2005, page 125. Fig.14: http://quizlet.com/6331453/biology-131-lab-midterm-1-flash-cards/ Fig.19: Adamatzky, Andrew and Jeff Jones. On Electrical Correlates of Physarum Polycephalum spatial activity: Can we see Physarum machine in the dark? Biophysical Reviews and Letters 6 (2011), p.4, p.14. Fig.20: Saigusa, Tetsu et al. “Amoebae anticipate periodic events.” Physical Review Letters 100.1 (2008), p.018101-2. Fig.21: http://lloydsnlondon.wordpress.com/2010/03/12/physarum-material-internet/ Fig.22: Pickering, Andrew. The Cybernetic Brain: Sketches in Another Future. Chicago ; London : Chicago University Press, 2010, page 338. Fig.23: http://article.wn.com/view/2011/10/25/profesor_j_zef_szyma_ski_by_y_rektor_ umcs_nie_yje/ Fig.24: Adamatzky, Andrew, Ben De Lacy Costello and Tetsuya Asai. Reaction-diffusion computers. Amsterdam ; Oxford : Elsevier, 2005, page 48. Fig.25: Chen, I. et al. “Shape- and Size-dependent patterns in self-oscillating polymer gels” Soft Matter 7, no.7, (2011) Fig.26: Walter, Walter Grey. “An imitation of life”. Scientific American, 182(5), (1950): 42. Fig.27: Ashby, Ross. Design for a brain, The origin of adaptive behaviour. London: Chapman & Haal, 1952, page 102. Fig.28: http://ars.els-cdn.com/content/image/1-s2.0-S0303264712000056-gr4.jpg Fig.29: http://www.haustechnikdialog.de/shkwissen/209/Thermostatischer-Wassermischer Fig.30: Walter, Walter Grey. The Living Brain. page 200. Fig. 31: Walter, Walter Grey. The Living Brain. page 51 . Fig.32: https://spie.org/x47370.xml?ArticleID=x47370 Fig.33: Pask, Gordon. Approach to cybernetics. London : Hutchinson, 1961, page 106. Fig.36: http://www.nature.com/nchem/journal/v2/n2/fig_tab/nchem.530_F1.html Fig. 37 :Yoshida, R. “Self-Oscillating Gel as Novel Biomimetic Materials” Journal of Controlled Release 140, no.3, (2009) Fig.38: Molecular design scale Fig.47: http://commonplacesarchitecture.wordpress.com/2011/07/03/talking-in-parablessuperstudios-narratives/ Fig.48: http://www.slideshine.de/2220/Mars%20atmosphaere.jpg?pageindex= Fig.49-51: http://arqueologiadelfuturo.blogspot.co.uk/2009/09/1971-12-ciudades-idealessuperstudio_27.html
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Bibliography Adamatzky, Andrew. Physarum machines : computers from slime mould. New Jersey : World Scientific Publishing, 2010. Adamatzky, Andrew, Ben De Lacy Costello and Tetsuya Asai. “Universal Computation with Limited Resources: Belousov-Zhabotinsky and Physarum Computers.” International journal of bifurcation and chaos in applied sciences and engineering. VOL 18; NUMB 8 (2008). Adamatzky, Andrew and Jeff Jones. “Programmable reconfiguration of Physarum machines.” Natural Computing Volume 9, 2009, Number 1, 219-23. Adamatzky, Andrew, Ben De Lacy Costello and Tetsuya Asai. Reaction-diffusion comput¬ers. Amsterdam ; Oxford : Elsevier, 2005. Adamatzky, Andrew and Jeff Jones. On Electrical Correlates of Physarum Polycephalum spatial activity: Can we see Physarum machine in the dark? Biophysical Reviews and Letters 6 (2011) 29-57. Adamatzky, Andrew. “If BZ medium did spanning trees these would be the same trees as Physarum built.” Physics Letters A. 372. no. 10 (2009): 952–956. Asai, Tetsuya, Yusuke Kanazawa, Tetsuya Hirose and Yoshi. “Analog Reaction-Diffusion chip imitating Belousov-Zhabotinsky Reaction with Hardware Oregonator Model.” International Journal of Unconventional Computing. Vol.1, (2005): 123-147. Ashby, William Ross. Introduction to cybernetics. London: Chapman & Hall, 1958. Belousov, B.P “A Periodic Reaction and its Mechanism” Oscillations and Travelling Waves in Chemical Systems, ed. Field, J.R and Burger, M (New York : John Wiley & Sons, 1985) Cariani, Peter. “To Evolve an Ear: Epistemological Implications of Gordon Pask’s Electro-chemical Devices”. Systems Research, 10(3), (1993) : 19-33. Casti, J.L. Complexification: Explaining a Paradoxical World Through the Science of Surprise (New York: Harper, 1994) Chen, I. et al. “Shape- and Size-dependent patterns in self-oscillating polymer gels” Soft Matter 7, no.7, (2011) : 3141-3146 Epstein, I.R Introduction to Nonlinear Chemical Dynamics ( New York , Oxford : Oxford University Press, 1998) Ermentrout, G.B. Edelstein-Keshet, L. “Cellular Automata Approaches to Biological Modeling.” Journal of Theoretical Biology 160, no.1, (1993): 97-133 43
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Bibliography Goodwin, B.C. How the leopard changed its spots (London: Weidenfeld & Nicolson,1994) Hamley, W. Introduction to Soft Matter – revised edition: synthetic and biological self-assembling materials (Chichester: John Wiley , 2007) Haque, Usman, “The architectural relevance of Gordon Pask”. 4d Social - Interactive De¬sign Environments, Architectural Design. London: Wiley & Sons (2007): 54-61. Hickey, D S, and L A Noriega. “Insights into Information Processing by the Single Cell Slime Mold Physarum Polycephalum.” con¬trol2008org (2008) : 565-569. Johnston, John. Allure of Machinic Life: Cybernetics, Artificial Life, and the New AI. Cam-bridge, MA : MIT Press, 2008. Jones, Jeff. “Characteristics of pattern formation and evolution in approximations of Physarum transport networks.” Artificial Life 16.2 (2010) : 127-153. Keller, E.F. Making Sense of Life : Explaining Biological Development with Models, Metaphors, and Machines (Cambridge : Harvard University Press, 2002) Kuksenok,O. Yashin,V.V. Dayal, P. Balazs, A. “Self-Oscillating Gel as Biomimetic Soft Materials” Nonlinear dynamics with Polymers : fundamentals, methods and applications (eds J. A. Pojman and Q. Tran-Cong-Miyata), (Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim, Germany, 2010):135-162 Lang, Peter, and William Menking. Superstudio: Life without Objects: . Skira, 2003. Matsumaru, Naoki, Florian Centler and Peter Dittrich. “Chemical Organization Theory as a Theoretical Base for Chemical Computing”. Proceedings of the 2005 Workshop on Unconventional Computing: From Cellular Automata to Wetware. Beckington: Luniver Press (2005): 75-88. Mayr, E. Toward a New Philosophy of Biology ( Cambridge, MA : Harvard University Press, 1988) Nakagaki, Toshiyuki et al. “Obtaining multiple separate food sources: behavioural intelligence in the Physarum plasmodium.” Proceedings of the Royal Society B Biological Sciences 271.1554 (2004) : 2305-2310. Pask, Gordon. “A Comment, a case history, a plan”. Reichardt, Jasia ed., Cybernetics, art and ideas. London: Studio Vista (1971): 76–99. Pask, Gordon. Approach to cybernetics. London : Hutchinson, 1961. Pask, Gordon. “The architectural relevance of cybernetics.”Architechtural Design. 9. (1969): 494-496.
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Pechenkin, A. “B P Belousov and his reaction” Journal of Biosciences 34, no.3, (2009) : 365371 Piaget, J. Structuralism ( London: Routledge and Kegan Paul,1971)v Pickering, Andrew. The Cybernetic Brain: Sketches in Another Future. Chicago ; London : Chicago University Press, 2010. Prigogine, I. The End of Certainty : Time, Chaos, and the New Laws of Nature (London: The Free Press, 1997) Saigusa, Tetsu; Tero, Atsushi; Nakagaki, Toshiyuki; Kuramoto, Yoshiki (2008). “Amoebae Anticipate Periodic Events”. Physical Review Letters 100 (1): 018101 Shanks, N. “ Modelling Biological Systems: The Belousov-Zhabotinsky Reaction” Foundations of Chemistry 3, no.1, (2001) : 33-53 Tsuda, Soichiro and Jeff Jones. The emergence of synchronization behavior in Physarum polycephalum and its particle approximation. Biosystems. Volume 103, Issue 3, March 2011, Pages 331–341. Tsuda, Soichiro, Jeff Jones, Andrew Adamatzky and Jonathan Mills, “Routing Physarum with electrical flow/current,” International Journal of Nanotechnology and Molecular Computation. Tsuda, Soichiro, Masashi Aono, and Yukio-Pegio Gunji. “Robust and emergent Physarum logicalcomputing.” Biosystems 73.1 (2004) : 45- 55. Tyson, J. J. “What everyone Should Know About the Belousov-Zhabotinsky Reaction” Lecture Notes in Biomathematics 100, (1994) : 569-584 Walter, Walter Grey. The Living Brain. London : Duckworth, 1953. Walter, Walter Grey. “Studies on Activity of the Brain”. Cybernetics: circular casual, and feedback mechanisms in biological and social systems. New York, NY (1953) : 689-696. Walter, Walter Grey. “An imitation of life”. Scientific American, 182(5), (1950): 42-45. Wiener, Norbert. Cybernetics: or the Control and Communication in the Animal and the Machine. Cambridge: The MIT Press, 1965. Winfree, A.T. “The Prehistory of the Belousov-Zhabotinsky Oscillator” Journal of Chemical Education 61, no.8, (1984) : 661-663 Yoshida, R. “Self-Oscillating Gel as Novel Biomimetic Materials” Journal of Controlled Release 140, no.3, (2009) : 186-193
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_ Architectural Critique _ Slime Mold Research _ Slime Mold Tests _ Digital Exploration _BZ Research _Digital Exploration _ Material Tests _ Slime Mold and Cybernetics
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Architectural critique / Building life cycle & tectonics
Fig.1: Material extraction, transportation and processing
Fig.2: Transportation distances AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Organisational systems The design and the assembly of building components is based on a system of fixed geometrical and numerical relationships. The measurement system is derived from human dimensions. The resulting measurement of the component is a multiplication of the basic module dimension in order to allow geometrical compatibility among different components. Components are organized within grid systems based on euclidean geometry. Furthermore, the measures of a building component is determined by structural material limitation and transport dimensions.
Fig.3: Anthropometric study, Ernst Neufert.
Fig.6: Preferred dimensions
Fig.4: Modules based on human measurement
Grids
Fig.7: Grids: dimensional coordination of elements
The relationship among constructional components gets geometrically and statically defined by an organisational grid system. The spacing of a grid determines the proportion of space, the assembly and the design of the building. There are different types of overlaid grid systems: structure, internal fitting, building envelope and services grid.
Fig.5: Module classification 49
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Architectural critique / Assembly/ Construction: Tectonic systems
Fig.8: Overview frame construction systems
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Fig.9: Overview solid construction systems
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Architectural critique / Usage Phase
Service life/ Lifetime of components The statistics on lifetime, service and maintenance -cycles of building components clearly visualize, that conventional building tectonics are composed of a variety of materials and components. These components not only have multifaceted qualities, but also have different tasks to fulfil. These aspects lead to variable lifetimes. With this information in mind, a polyvalent building system composed of minimal, but performative components and materials seems to be a more appropriate approach.
Fig.10: Service life and Lifetime of components AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Fig.11: Maintenance cycles
Maintenance intervals in years
Fig.12: Service life building services 53
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Architectural critique / Demolition & Waste Demolition and waste The statistical analysis clearly shows that building waste takes up a large part of the general waste production. Within this segment, demolition and renovation waste take up a major part. This is because building components have a limited life-time and their technical level becomes obsolete after a certain usage phase. This fact demands a more cyclic approach towards materials and building systems considering self-repair and inherent emergent/ transformative matter qualities.
Fig.13: Ratio construction and demolition debris Characteristic of building-related construction and demolition in the United States, U.S EPA, 1998.
Fig.14: Distribution of waste in general
Fig.15: Origin of debris
Fig.16: Distribution of waste in accordance with types and reuse quota, 2007
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Recycle and reuse In order to reuse material components or the embedded energy, further energy has to be put into the material system and manual, chemical and physical operations have to be applied. These operations are expensive and operationally elaborate. The reusability of matter therefore needs to be inherently considered within the design of a material or building system.
Fig.17: Accrual and recycling of building waste
Fig.18: Examples of recycling
Fig.19: Examples of reuse 55
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Architectural critique / Conclusion
The initial analysis on conventional, static and geometrically defined building systems led to the search for dynamically self-organizing and self-structuring systems of polyvalent nature. The slime mold, being an inherently polyvalent and self-organising system, fits well into the studio agenda. The slime mould is not seen as a mere reference and the main focus does not lie in imitating physically apparent features such as the network morphology. The intention is to extract the organizational logic hidden behind the capability of dynamic matter aggregation- principles not visible to the naked eye. Our approach is of the algorithmic logic, not geometric. We are more focused on its behaviour and its intelligibility. This is a fundamentally different behaviour to that of the current architectural tectonic principles of inflexible and separate parts, that lacks adaptive capabilities and often becomes redundant – not even being able to entirely fullfill the promised functionality of the modernist sense. Hence we have researched into materials of adaptive and flexible potentials contradistinctive to the building materials of the past and the current.
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Architectural critique
References Deplazes, Andrea. Constructing architecture : materials, processes, structures : a handbook. Basel : Birkhauser, 2008. Hegger, Manfred, Matthias Fuchs, Thomas Stark and Martin Zeumer. Energy Manual : sustainable architecture. Basel : Birkhauser, 2008. Hegger, Manfred, Matthias Fuchs, Thomas Stark and Martin Zeumer. Construction materials manual. Basel : Birkhauser, 2006. Staib, Gerald, Andreas Dรถrrhรถfer and Markus Rosenthal. Components and systems : modular construction ; design, structure, new technologies. Basel : Birkhauser, 2008. Detail Heft 12/2010. Architektur und Recycling. Titlepage: Staib, Gerald, Andreas Dรถrrhรถfer and Markus Rosenthal. Components and systems : modular construction ; design, structure, new technologies. Basel : Birkhauser, 2008, p.55.
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Image Credits Fig.1: http://science.nationalgeographic.com/wallpaper/science/photos/rocks/marble-quarry/ http://www.flickr.com/photos/13681710@N02/4021834292/ http://www.osbornlondon.co.uk/Storage.html http://www.flickr.com/photos/atelier79033/2848897573/in/photostream Fig.2: Staib, Gerald, Andreas Dörrhöfer and Markus Rosenthal. Components and systems : modular construction ; design, structure, new technologies. p.45. Fig.3: http://www.architekturbuero-spath.de/das-b%C3%BCro/ Fig.5: Staib, Gerald, Andreas Dörrhöfer and Markus Rosenthal. Components and systems : modular construction ; design, structure, new technologies. p.44. Fig.4, 7: Staib, Gerald, Andreas Dörrhöfer and Markus Rosenthal. Components and systems : modular construction ; design, structure, new technologies. p.44. Fig.6: Staib, Gerald, Andreas Dörrhöfer and Markus Rosenthal. Components and systems : modular construction ; design, structure, new technologies. p.45. Fig.8, 9: Staib, Gerald, Andreas Dörrhöfer and Markus Rosenthal. Components and systems : modular construction ; design, structure, new technologies. p.55-71. Fig.10: Hegger, Manfred, Matthias Fuchs, Thomas Stark and Martin Zeumer. Energy Manual : sustainable architecture. Basel : Birkhauser, 2008, p. 23. Fig.11: Hegger, Manfred, Matthias Fuchs, Thomas Stark and Martin Zeumer. Energy Manual : sustainable architecture. p. 12. Fig.12: Hegger, Manfred, Matthias Fuchs, Thomas Stark and Martin Zeumer. Energy Manual : sustainable architecture. p. 53. Fig.13, 14, 15: Design for Deconstruction: The Chartwell School Case Study. U.S EPA, 1998, p.9. Fig.16: Detail Heft 12/2010. Architektur und Recycling, p.1342. Fig.17: Detail Heft 12/2010. Architektur und Recycling, p.1344. Fig.18: Detail Heft 12/2010. Architektur und Recycling, p.1273, 1278, 1348. Fig.19: Detail Heft 12/2010. Architektur und Recycling, p.1343-1352.
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Slime Mold Research
Classification Due to its physical structure, the slime mould belongs to the family of Eucaryas (Amoebas). It has real nuclei as well as membrane encapsulated organelles and plasma. The motile slime mould cannot be classified as an animal but being unicellular it belongs to the group of Protists. There are two major distinctions: Myxomycetes and Dictyostelids. Within the family of slime moulds, there are roughly 1000 species. The particular species of interest is the Physarum Polycephalum. The word “poly” means many and “ cephalum” means head.
Fig.1: Classification Slime Mould AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Cellular and true slime mould There are two major families of slime moulds: The cellular (Dictyostelids) and the true slime mould (Myxomycetes). Within the cellular slime mould, the decision-making processes is lead by a hierarchical cell organization. Furthermore, the fusion of amoebae leads to a slug soon meant to develop into a fruiting body. In case of the true (multiheaded) slime mould there is no hierarchy among the identical amoebae fusing to one multinuclear single cell. The information processing and decision-making is based on collective and synchronized behaviour. The evolved multinuclear cell of the plasmodium stage migrates during the foraging process until unfavourable conditions lead to the development of the fruiting body.
Fig.2: Type distinction cellular and true slime mould 61
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Life Cycle The life cycle of the Physarum polycephalum is continuous. Within the life cycle, smatter and genetic information never decays. Depending on environmental conditions and the need for survival, matter changes its aggregate state and its physicality.
Fig.3: Life cycle AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
A) Fruiting body
D) Swarm cell
A) Bursting fruiting body
D) Fusing swarm cells
Spores
G) Plasmodium
B) Germination
H) Scelortium 63
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Amoeboid fusion When the population of individual amoebae faces the depletion of food sources and dehydration, migration is required for acquiring new food sources. Since a single amoeba is not able to migrate, a collective and collaborative cellular fusion is the key for survival. The fusion process demands chemical signalling and sensing one another by the chemical secretion of “CAMP”. As the amoebae move and aggregate towards the higher concentration of “CAMP”, the chemical secrete is an attractant for other amoebae. The chemical signalling leads to the coordinated behaviour and movement of the individual amoebae forming a large communicative amoeboid cell, the multi- nuclei plasmodium capable of migration. After the fusion process, the chemical attractant breaks down due to chemical reaction. The fusion process is nonlinear and instable, as it is based on the interplay of the diffusive mobility of the amoebae, the production of the attractant and the decay of the attractant.
Fig.4: Amoeboid fusion
Reaction-Diffusion as a means of information processing As the Physarum polycephalum is an excitable media encapsulated in a flexible growing membrane, it is equivalent to a Reaction-Diffusion chemical computer in terms of its way of information processing. The principle of the computational process and the information processing is the autocatalytic and self sustained Reaction-Diffusion Reaction. The capability to process information is a key for survival. The data input is of chemical nature and can be considered as perturbation to the nonlinear dynamic system. If environmental and physical conditions are favourable, computation and thus information processing does not stop, even if there are no more data inputs. The excitation travels in waveform and determines the trajectory of propagation and the formation of the slime mould. The morphological transformation and the decision-making process can be mathematically described by the Oregonator Model of the Belousov- Zhabotinsky Reaction. The activator, the value u, equals the concentration of the cytoplasm at the propagating wave front. The inhibitor, the value v, is a combination of the following factors : rate of nutrient consumption, byproducts of chemical chains ignited by signals on photo- and chemoreceptor and concentrations of metabolites released by the plasmodium into substrate. The values u and v are based on a time scale by the parameter €. The parameter q scales the reaction rates and f is a stoichiometric coefficient. The result of this process is physically exhibited by the dynamically changing morphological character. The constantly changing morphology means that memory and matter are reusable due to the inherent capability of dynamic information processing. This constant process leads to a cyclic change of the chemical nature of matter.
Fig.5: Oregonator model BZ-reaction AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Encoded messages
Fig.7: Measuring action potentials
The biological way of information processing is abstractly based on sensing information and developing a response. The global communication within the Physarum polycephalum is based on oscillating patterns, which serve as encoded messages. The generation of these distinct patterns is based on stimuli (chemo-attractants/-repulsions), which serve as perturbations to the nonlinear excitable system of the slime mould. The information processing within the Physarum is based on excitability, whereas the process can be described by Reaction-diffusion. The oscillation pattern can be manipulated by altering the chemical field of an environment. The frequency of an oscillating rhythm increases in the event of an attractive stimulus and decreases, if the stimulus is repulsive. The emergence of the oscillating rhythm is closely connected to structural changes within the plasmodium. Structurally, the plasmodium is composed of an ectoplasm tube, which is a gel membrane layer, enclosing an endoplasmic core, the fluid state of the protoplasm. The structural change within the ectoplasm tube regarding the aggregation of cytoplasmic actomyosin generates a hydrostatic pressure. This eventually lead to the ectoplasmic flow ( shuttling) from one location of the cell to another and back determining the rhythm of the oscillating pattern. Physically, the frequency of oscillation is described within the slime mould by the protoplasmic streaming. The oscillating pattern equals the action potential of a brain, whereas its electric activity and the oscillatory pattern is measurable, as it is the oscillation of calcium ion concentrations.
Fig.6: Information processing: Reaction diffusion patterns 65
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Global and Local The slime mould executes high level global commands as a whole at once, whereas local commands are processed by local parts of the plasmodium. The Physarum is capable of processing the information of multiple stimuli simultaneously in a spatially distributed manner. The oscillatory pattern leads to (locally) synchronized behaviour and the generation of differentiated physical patterns. Local phase patterns lead to the emergence of a global phase pattern within the cell, which determines the overall behaviour of the organism such as the direction of migration. On the other hand, a globally synchronized rhythm can be desynchronized, when a local part of the cell is exposed to external stimulus. If the amoeboid cell is not perturbated by any external stimuli, the contractile rhythm remains synchronized within the cell. This fact leads to the comparison with the Kolmogrov-Uspensky machine, which acts depending on the state of the neighbourhood. Therefore one can perceive multiple oscillation patterns within one cell. The distributed information processing optimizes food gathering strategies.
Fig.8: Information processing
Characteristics of matter The Physarum Polycephalum is excitable, soft matter encapsulated in an elastic expanding membrane. The main components of the heterogeneous mass are the ectoplasm tube, which is a gel membrane layer, enclosing an endoplasmic core, the fluid state of the protoplasm.
Morphology The initial stage of the growth process is a random spread, which is due to the vital search for chemo-attractants. Matter accumulates in location of chemo-attractants. The pattern formation process and the specific topology are the physical translation of the encoded message of the oscillatory pattern (action potential). The oscillatory patterns are generated stimuli based, whereas their specificity suggests that the slime mould can distinguish between qualitative different environmental chemo-attractants. This physically expressed behaviour can be morphologically transformed and “controlled” by the setup and the chemical nature of the environment. There are a variety of patterns, which include excitation waves, tree-like protoplasmic networks/ tubes and resting patterns. Excitation waves can be observed on a nutrient rich environment, as excitability is displayed when an environment offers a high - nutrient level. Therefore the slime mould distributes more “matter”, as more energy can be absorbed. Localized wave fragments and tree-like structures can be observed on a low-nutrient substrate. As less energy can be absorbed and sensed, less AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Fig.9: Excitation waves in nutrient rich environment
Fig.10:Skeletal veins connecting food sources and tree like structure on non-nutrient surface
Fig.11:wave fragments on low-nutrient surface
Fig.12: Resting pattern
Fig.13: Gradually thickening tube with decreasing straightness due to a change in the oscillatory pattern encoding information
Fig.14: Mathematical model for network formation
matter is aggregated. Rather than spreading, the slime mould generates travelling localizations. Skeletal tree structures and material saving connections of food sources can be observed on non-nutrient substrates. A resting pattern can be seen as a result of a successful computational process or if no additional chemo attractants can be detected. The dyntamic physical structure is the result of a computational process. Computation is therefore immediately expressed formally. Furthermore, every morphological expression is capable of fulfilling a vital task. This concludes to the fact, that the slime mould combines hardware (body) and software (brain) in one.
Fig.15: Mathematical model for tubular structure
Physical rules
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structural
The structural development of protoplasmic tubes is depended on the sheer stress produced by the cytoplasmic streaming driven by rhythmic contractions. Therefore there is a constant feedback between the thickness of the tube and the intensity of flux. The higher the flux, the thicker the tubular structure. The protoplasmic tubes are formed at the areas of the highest oscillatory activity, whereas tubes are abandoned once the oscillatory activity disappears.
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The active zone The active zone (pseudopodia) is the computational head of the Physarum Polycephalum. By the leading fan like active zone, the body of the slime mould gains a directionality. Skeletal veins form the lagging end. In search of chemo-attractants the active zone of the slime mould constantly explores its environment, which means that due to the foraging behaviour computation never halts. The exploratory behaviour suggests the presence of inbuilt sensors. These enable the slime mould to scan its environment for chemo-attractants, which crucial for survival. This phenomena explains the strong sense of navigation, e.g. observed when placing the mould in a maze. When no chemo attractants are found in an environment, the plasmodium exhibits a disorganized and random exploratory behaviour. Thus, the decision-making process is a consequence of scanning the environment for chemical stimuli. This process can be computationally described by the binary logic.
Fig. 17/ 18:The active zone
Fig.19:The active zone exploring its environment for chemoattractants AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Learning and Memory
Learning: Active zone
Learning is a result of the exploratory process, which takes place in the computational head. The Physarum is capable to learn from periodic events and in anticipation modify its behavioural patterns. Furthermore, the occurrence of (cytoplasmic) waves is associated with learning, as these lead to the synchronization of oscillatory patterns with the overall body. Inactive and “frozen� structures such as tubular connections between nodes are memory. Abandoned white tubes can be seen as long term written memory. Even the sclerotium phase can be seen as long term memory.
Memory: Tubes connecting nodes
Fig.20: Learning and memory Dynamic
Stationary node
Fig.21: Learning and memory details a
b
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The physical expression of the computational head can be operatively manipulated and altered by adding or altering the chemical fields of an environment. By doing that, two active zones can fuse to one, one active zone can split into two, new active zones can evolve out of inactive nodes and two active zones can fuse and therefore get deactivated. That strongly indicates that sensory features are not only located within the computational head but within the whole body, which enables a spatially distributed computational processes. In that way, the physical expression can be constantly restructured.
Manipulative operations a) Two active zones fusing to one active zone b) Two active zones fusing to an inactive tube c) One active zone splitting up into two active zones Fig.22: Manipulating the active zone
d) Two new active developing out of a nodal point 69
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Foraging process The need for survival leads to collaborative behaviour. Once a food-source is found the slime mould covers the source and discharges enzymes for the digestion. The nutrients are passed to remote parts of the body by the cytoplasmic flow . The constant search for more chemo-attractants is a crucial part of the survival instinct.
The brain: Cellular “memory�
Fig.23: Slime mould connecting food sources and exploring the environment for more chemoattractants
Fig.24: Slime mould covering food source
The multiheaded amoeboid large cell is a decentrally organized single cell. The time based evaluation of behavioural patterns reveal the intrinsic capability to learn and anticipate events.
Anticipation of events If stimuli appear periodically, the slime mould is capable of anticipating these events. The diagram confirms the fact, that repeated stimuli such as cool and dry air in intervals of 60 minutes cause the organism to decrease its growth after the next period even without the stimulation. After a few periods however the response disappears, but can be reanimated by a single additional stimulation. This feature suggests, that information about past states is stored and can be accessed. The anticipation lies in the change of behaviour at the time a periodic change was next due to occur, even when the environmental change does not occur. This characteristic can be considered the nonphysical form of memory. The fundamentals for the anticipatory behaviour are not yet discovered but believed to be the result of the natural biochemical oscillations within the organism. These interact over a distance by diffusing and lead to the synchronization of a phase.
Fig. 25, 26, 27: Microscopic view of information and nutrients being passed through protoplasmatic tubes
Fig.28: The multiheaded Physarum
Fig.30: The anticipation of a periodic stimulus
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Fig.29: Multiple nuclei
Solving the maze When food-sources are placed at the entrance of a maze, the slime mould is capable of solving the maze. This fact displays the power of cellular information processing as well as their ability to sense chemo-attractants. Both features are key reasons for the navigational capability of the Physarum. Fig.31: Solving the maze
Fig.32: Slime mould mimics Tokyo’s rail network
Efficient paths & networks The fact that the slime mould can approximate the shortest path and efficient network structure allows the efficient transport of information and nutrients within the cell. The shortest paths physically remain as thick and short tubes. According to hydrodynamic theory this topology is the most effective for transportation, as both physical features allow increasing the flux and therefore the quickest exchange of nutrients and chemical informational signals. This strategic physicality maximizes the performative survival tasks. During the optimization process open-ended tubes disappear, while the traces of their existence can still be perceived by white remaining marks. The formation of tubular structures depends on the direction of the protoplasmic shuttle streaming, which is driven by the hydrostatic pressure induced by rhythmic contraction. This shuttle streaming needs to persist in a specific direction for a tube to develop. Structurally, the self-organized tubes consist of actomyosin fibres oriented along the stretching force that results from cytoplasmic streaming. Forces inside the organism lead to the structural self organization of the tubes, whereas a higher degree of oscillatory frequency leads to thicker tubes. Furthermore, the pattern of contraction rhythm is crucial for the morphology of the network. Within one plasmodium cell various patterns of spatiotemporal variations in relation to altering plasmodium streaming can be observed. This suggests that pattern formation is dynamic and can differ spatially which is due to the spatially distributed computation.
Steiner minimum tree When several food sources are presented, the Physarum can approximate the Steiner’s minimum tree route to connect the food sources. Mathematically seen, Steiner’s minimum tree is the shortest route connecting a network structure. Therefore, the slime mould forms cyclical networks (CYC), which geometrically express efficiency in communication. However, the slime mould does not find SMT-like solution precisely.
Fig.33, 34: Steiner minimum tree approximation
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Cellular robot control This approach utilizes the capability of the Physarum Polycephalum as an information processor. Despite being a single cell, the slime mould is able to conduct (spatially) distributed information processing. Thus, biological modes of information processing are more elaborate, but not yet fully understood. By fusing artificial hardware and biological control systems for real time responses, a hybrid, autonomously behaving engineered device is generated. This prototypical approach can create adaptive behaviour in engineered systems, whereas utilizing the moulds communicative and responsive behaviour to external stimuli is the key idea of this device. The design of the hybrid device foresees the integration of a plasmodium into a robot by coupling it to the robot’s environment via bidirectional interfaces. The robot is controlled by the contractile oscillation dynamics of the cell. The sensory data of an external light input is received by the robot and utilized to generate stimulating signals to the Physarum cell. The resulting oscillatory activity is transferred back to the robot and interpreted as source of control signals for the life-like autonomous robot.
Fig.35: Cellular robot design
Fig.36: Feedback loop AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Physarum biosensor chip In a technically more advanced prototype, the artificial device is controlled by a biochip which encapsulates a plasmodial cell of the slime mould Physarum polycephalum. The computing brain yet again becomes the software of the artificial hardware. The EIS (electrical impedance spectroscopy) is interface for measuring and accessing the molecular computing process as well as the oscillatory activity in presence of light. The biosensor chip is capable of sensing other chemo-attractants of the environment as well. The behaviour of the plasmodium is encoded in form of oscillation data and decoded into robotic mechanic signals.
Fig. 37: Physarum biosensor chip
Opportunities In prototypes to be developed in future the sharp distinction between the artificial and the animate world needs to be overcome. In consequence, the traditional distinction between hardware and software would become obsolete. This approach could lead to the development of an architecture free engineered device comprising artificial and animate components. Furthermore, these approaches lead to the reconsideration of information theory and the means of encoding and decoding information. In the case of the slime mould, information is encoded within the oscillatory pattern and decoded by behaviour.
Fig.38: Translating the action potential 73
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References Adamatzky, Andrew. Physarum machines : computers from slime mould. New Jersey : World Scientific Publishing, 2010. Adamatzky, Andrew, Ben De Lacy Costello and Tetsuya Asai. “Universal Computation with Limited Resources: Belousov-Zhabotinsky and Physarum Computers.” International journal of bifurcation and chaos in applied sciences and engineering. VOL 18; NUMB 8 (2008). Adamatzky, Andrew and Jeff Jones. “Programmable reconfiguration of Physarum machines.” Natural Computing Volume 9, 2009, Number 1, 21923. Adamatzky, Andrew and Jeff Jones. On Electrical Correlates of Physarum Polycephalum spatial activity: Can we see Physarum machine in the dark? Biophysical Reviews and Letters 6 (2011) 29-57. Adamatzky, Andrew and Maciej Komosinski. Artificial Life Models in Software. London: Springer, 2009. Jones, Jeff. “Characteristics of pattern formation and evolution in approximations of Physarum transport networks.” Artificial Life 16.2 (2010) : 127153. Hickey, D S, and L A Noriega. “Insights into Information Processing by the Single Cell Slime Mold Physarum Polycephalum.” control2008org (2008) : 565-569. Nakagaki, Toshiyuki et al. “Obtaining multiple separate food sources: behavioural intelligence in the Physarum plasmodium.” Proceedings of the Royal Society B Biological Sciences 271.1554 (2004) : 2305-2310. Tsuda, Soichiro and Jeff Jones.The emergence of synchronization behavior in Physarum polycephalum and its particle approximation. Biosystems. Volume 103, Issue 3, March 2011, Pages 331–341. Tsuda, Soichiro, Masashi Aono, and Yukio-Pegio Gunji. “Robust and emergent Physarum logical-computing.” Biosystems 73.1 (2004) : 45-55. Tsuda, Soichiro, Klaus-Peter Zauner, and Yukio-Pegio Gunji. “Robot Control: From Silicon Circuitry to Cells.” Science And Technology. Ed. A J Ijspeert, T Masuzawa, & S Kusumoto. Springer, 2006. 20-32.
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Image credits Titlepage: http://www.flickr.com/photos/randomtruth/4350484166/ Fig. 1: http://bio.fsu.edu/~stevet/pictures/TheBigTree.jpg. Fig. 3: Adamatzky, Andrew. Physarum machines : computers from slime mould. New Jersey : World Scientific Publishing, 2010, p.7. http://www.seenby.de/oliver-meckes/myxo-2 http://www.sciencephoto.com/media/13916/enlarge http://www.sciencephoto.com/media/13932/enlarge http://www.botany.hawaii.edu/faculty/wong/Bot201/Myxomycota/Myxomycota.htm http://www.es.hokudai.ac.jp/labo/cell/index_e.html Fig. 5: Adamatzky, Andrew. Physarum machines : computers from slime mould. p.56. Fig. 6: http://www.youtube.com/watch?v=l6kyE_cct-0 (images extracted from video) Fig. 7: Adamatzky, Andrew and Jeff Jones. On Electrical Correlates of Physarum Polycephalum spatial activity: Can we see Physarum machine in the dark? Biophysical Reviews and Letters 6 (2011), p.4, p.14. Fig. 9: Adamatzky, Andrew. Physarum machines : computers from slime mould. p.31. Fig. 14, 15: Tero, Atsushi, Ryo Kobayashi, and Toshiyuki Nakagaki. “A mathematical model for adaptive transport network in path finding by true slime mold.” Journal of Theoretical Biology 244.4 (2007). p.6. Fig. 16: Tero, Atsushi, Ryo Kobayashi, and Toshiyuki Nakagaki. “A mathematical model for adaptive transport network in path finding by true slime mold.”. p.4. Fig. 21: Adamatzky, Andrew. Physarum machines : computers from slime mould. p.112. Fig. 22: Adamatzky, Andrew. Physarum machines : computers from slime mould. p.126. Fig. 25, 26, 27: http://lloydsnlondon.wordpress.com/2010/03/12/physarum-material-internet/ Fig. 29: http://quizlet.com/6331453/biology-131-lab-midterm-1-flash-cards/ Fig. 30: Saigusa, Tetsu et al. “Amoebae anticipate periodic events.” Physical Review Letters 100.1 (2008), p.018101-2. Fig. 31: Tero, Atsushi, Ryo Kobayashi, and Toshiyuki Nakagaki. “A mathematical model for adaptive transport network in path finding by true slime mold.”. p.5. Fig. 32: http://www.treehugger.com/cars/mold-may-help-design-future-transportation-routes.html Fig. 33: Nakagaki, Toshiyuki et al. “Obtaining multiple separate food sources: behavioural intelligence in the Physarum plasmodium.” Proceedings of the Royal Society B Biological Sciences 271.1554 (2004). p. 2307. Fig. 34: Nakagaki, Toshiyuki et al. “Obtaining multiple separate food sources: behavioural intelligence in the Physarum plasmodium.” . p. 2308. Fig. 35: Tsuda, Soichiro, Klaus-Peter Zauner, and Yukio-Pegio Gunji. “Robot Control: From Silicon Circuitry to Cells.” Science And Technology. Ed. A J Ijspeert, T Masuzawa, & S Kusumoto. Springer, 2006. p.28. Fig. 36: Tsuda, Soichiro, Klaus-Peter Zauner, and Yukio-Pegio Gunji. “Robot Control: From Silicon Circuitry to Cells.” . p. 25. Fig. 37: Adamatzky, Andrew and Maciej Komosinski. Artificial Life Models in Software. London: Springer, 2009, p. 222.
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Slime mold Tests / Preparation
In order to understand the behaviour of the object of research more profoundly and to extract the potentials for the design of architectural building systems, a wide range of slime mould tests are conducted. While some tests are supposed to be subcultures, the majority of tests were intentionally designed in order to analyse the behaviour expressed in form of dynamic matter reorganization. The behaviour is steered by chemo-attractants (oats), chemorepellents (salt) and light. Besides setting up the chemical field of a test, the quality of the actual substrate is crucial as well. The nutrient level of these environments ranges from no, low to high, whereas theses differences are clearly reflected within the behaviour of the slime mould. Other important factors are temperature and sufficient humidity. The test containers are stored in a dark space and only exposed to light for observation and daily documentation. As we are not intending to study the physical features, we have placed heavy focus on the studying these organisims, subjecting them to various different conditions within various test setups. The research into these organisms must aim to draw out the maximum potential applicable in design.
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Slime mold Tests / Tests
Survival
Test 07: Subculture Petri dish 9 cm 2% Agar
The slime mould exhibits exploratory behaviour when the source of chemoattractants is limited. While propagating as a whole body, a distinct active zone with a skeletal trail can be observed. A rather resting pattern emerges when a sufficient supply of chemoattractants is available.
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Traces of existence
Test 08: Subculture Petri dish 9 cm 2% Agar
Initially “individual� cells merge to one body, which propagates as a whole to explore its environment for chemoattractants. After a few days of testing, it is clear that matter can constantly reorganize itself, whereas the traces of a previously important structure can be perceived as white tubes.
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Slime mold Tests / Tests
Test 04: Scelotarium Petri dish 9 cm 2% Agar/ Wet filter paper
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Slime mold Tests / Tests
Reusable memory Over the course of time, systems can be completely reconfigured depending on the changing design of the chemical environment.
Test 09: Subculture Petri dish 9 cm 2% Agar
As matter responds to this by a constantly changing configuration, the computational memory and matter seem to be reusable.
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Redundancy
Test 10: Subculture Petri dish 9 cm 2% Agar
The slime mould is capable of rearranging matter in an economical way by developing material efficient tubular structures in order to connect the food sources. In this way redundancy is avoided.
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Test 11: Attractor edges, slime mould center Petri dish 9 cm 2% Agar
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Test 12: Repellents only, Petri dish 9 cm 2% Agar
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Slime mold Tests / Tests Observations: Light When the slime mould is exposed to white and blue light, it exhibits negative photo-taxis. This response is based on the heterogenous slime mould “matter� containing phytochrome-like pigments leading to a chain of biochemical processes in context with light. Light-based control is useful mainly for shaping the protoplasmic network. The stimuli of light and changing environments in general lead to the modification of the currently existing oscillatory pattern, which is the encoded message of the system. This is the basic principle for the behaviour to change, which is visually expressed by morphological changes. As a consequence the slime mould moves away from light and in context with starvation switches to another phase of its life cycle (sporulation). By doing this, it preserves its genetic data for coming generation. The sensitivity of the system with its susceptibility to perturbations and the heterogeneity of the matter indicate that behaviour can be programmed.
Test 16: Light as an obstacle Petri dish 9 cm 2% Agar
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Observations: Chemo- repellents
14.03.2012: 3D growth
The propagation of the active zone can be routed and manipulated by repellents and attractors. Within this test sodium chloride is placed on the substrate and serves as impenetrable obstacle. The intensity of the repellent forces the slime mould to grow three-dimensionally. However, dynamic programming is limited, since chemorepellents can not be removed from the substrate.
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Test 15: Attractor enclosed by repellent Petri dish 9 cm 2% Agar Oat flakes enclosed by salt
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Slime mold Tests / Tests
Test 17 Attractor-center, slime mold edges Petri dish 9 cm 2% Agar
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Test 20 Two environments Petri dish 9 cm 2% Agar/ 100 % Agar
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Information processing
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We areRESEARCH focusing on the information processing capabilities of the slime mould, which depend on its sensory features able to sense environmental stimuli. This computational process results in a dynamically changing organizational logic and matter distribution. In order to explore the sensory features and the physical expression of information processing physical tests dealing with extreme were realized. The environments are designed to be chemical fields, which can be seen as data inputs for computation.
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Electrical field When the slime mould is put into an electrical field, it directionally migrates towards the positive electrical charge (cathode).
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Global and Local As there is no hierarchy between local and global computational tasks, the slime mould is capable of processing the information of multiple stimuli simultaneously in a spatially distributed manner. The distributed information processing optimizes solving tasks crucial for survival.
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Digital Exploration / Concept
In order to simulate the behaviour of the slime mould in processing, behavioural aspects and scenarios are isolated.
In this simulation, each cell nucleus drops a chemical signals. And the cell nucleus also “sniff” ahead, trying to follow the gradient of other cell’s chemicals. Then, as time goes on, following these simple rules, the strong part became stronger, the weak part disappears eventu-ally.
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Digital Exploration / Catalogue
Diverse max speed
MAX_SPD= 0.10
MAX_SPD= 0.30
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MAX_SPD= 2.00
MAX_SPD= 3.00
MAX_SPD= 5.00
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WAN_MAG = 7.00
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Diverse wander magnitude
WAN_MAG = 0.10
WAN_MAG = 3.00
WAN_MAG = 5.00
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Diverse updating rate of CAMP signal
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Digital Exploration / Catalogue
Scenario 01: Multiple attractors around
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Scenario 02: One attractor at center
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Digital Exploration / Catalogue
Scenario 03: Lights as obstacles
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Scenario 04: Obstacles and Attractors
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Digital Exploration / CA like system
We are interested in developing an architecture for modelling emergence in cellular-automaton-like systems. We introduce an architecture in which mobile processes (MPs) are used to tag emergent properties on a cellular grid, thus identifying them at an upper layer. Some of the operational logic can be transferred to the MPs, providing downward causation to the lower layer grid, thus making the lower layer simpler than one implemented as a pure cellular automaton (CA). We also introduce the idea of rule migration, as a means of translating the simpler MP models into pure CA models.
A schematic illustration of the MP architecture used in the platelet model. The square grid represents the lower environmental layer, and arrows indicate the communication channels. The grey circle is a MP at the upper layer, and the grey square is a reflection of the state information that records its presence at the lower layer.
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Data Map
Trail Map
stores problem dataset and agentpositions
stores diffusing food source stimuli and agent trails
Configuration Data Projection
Agent Autocrine Sensory / Deposition Behaviour
A layered approach is used: As well as the data landscape layer where the environment configuration is stored and the agents reside, other data structures, identical in size and corresponding to the coordinate system of the data layer, may be used. These separate layers are used to represent the projection of hazardous stimuli to the population (not described in this article) and to store the chemotactic stimuli that the agents both deposit and follow (thetrail layer)
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Digital Exploration / Algorithm expresses
The generalmorphology of an agent and its basic underlying algorithm is illustrated in the figures. An agent occupies a single discrete location in the environ-ment, corresponding to a single pixel of a digitized image. Each agent is typically initialized at a randomly chosen unoccupied and habitable location and with a random orientation (from 0 to 360 deg, freeing the agent from the restrictive architecture of the underlying discrete image). The agent receives chemotactic sensory stimuli from its environment (chemoattractant levels stored in the trail map) via three forward ensors, and the agent responds to differences in the local environment chemoattractant levels by altering its orientation angle by rotating left or right about its current position. Although specified in nonlinear algorithmic terms (IF-THENstatements), the particle algorithm corresponds simply to cellular behaviors of chemoattraction, orientation, and persistent movement. It should be noted that, in relation to typical agent-basedmodels, the offset sensor distance is large (compared to the agent body size) and would nor-mally correspond to remote sensing behaviors. In this instance, however the offset distance mimics the overlapping actin-myosinmesh of the plasmodiumgel system. The offset sensor design generates signifi-cant sensory local coupling between the agent population (the sensory input of one agent can be strongly affected by the actions of nearby agents).
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Digital Exploration / Algorithm expresses
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Digital Exploration / Algorithm expresses
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BZ Reaction Diffusion Research
BZ Reaction Diffusion Wave Propagation
Vladimir Yevgenyevich Zhabotinsk and Boris Pavlovic Belousov
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
The Belousov-Zhabotinsky reaction is a chemical reaction which is a causal model for complex biological systems. Despite the difference in ‘constitution and composition’ 1 comparative to its biological archetype the reaction successfully produces phenomenological similarities. The Belousov-Zhabotinsky reaction demonstrates behaviours that are difficult to translate into digital computation due to its complex interplay of travelling local rules that respond to a larger scale global rule within a non-hierarchical system. This reaction has proliferated in the field of material sciences where this chemical reaction is directly applied. The significance of this is the subtraction of exterior control of the material physicality, and the reaction itself is inherent in the material substance which becomes a fundamental constituent of the resultant behaviour. Belousov-Zhabotinsky (BZ) reaction was initially observed in the 1950s by a Russian chemist Boris Pavlovic Belousov during his attempt to simulate the Krebs (citric acid) cycle. It was a ‘chemical model of the oxidation of organic molecules in living cells’ 2, which demonstrates the metabolic processes found in nature. Belousov described his observations as a “homogenous reaction connected with a periodic change in colour of an entire reaction mixture: from colourless to yellow and back to colourless.” 3The BZ reaction displays spatiotemporal phenomena through its oscillating behaviour. Despite the current recognition of its importance, the homogenous oscillatory reaction was met with much resistance among the scientific community in Moscow as “all felt that chemical oscillation constituted a violation of the Second Law of Thermodynamics 4 .”5 Instead of a linear chemical reactionary process that will inevitably reach a static equilibrium the idea of a continued self-generating oscillation was a challenging proposal. Belousov’s original papers presenting this reaction were rejected by all the main chemical journals in the 1950s, and he was only able to publish an abstract of his findings in an “unrefereed proceedings of a conference on radiation medicine.” 6 This reaction remains obscure in the West until the late 1960s when Anatol Zhanbotinsky refines the reaction and presents it at the 1968 Symposium on Biological and Biochemical Oscillators7. Although Zhabotinsky was continuously in contact with Belousov of the reaction’s progress the two never met. There are now several recipes for the BZ reaction, but fundamentally it is a “chemical reaction in which an organic substrate is oxidized by bromate ions in the presence of a transition metal ion. The reaction is carried out in acidic solution.” 8
1 Shanks, N. “ Modelling Biological Systems: The Belousov-Zhabotinsky Reaction” Foundations of Chemistry 3, no.1, (2001) : 44 2 Tyson, J. J. “What everyone Should Know About the Belousov-Zhabotinsky Reaction” Lecture Notes in Biomathematics 100, (1994) : 569 3 Pechenkin, A. “B P Belousov and his reaction” Journal of Biosciences 34, no.3, (2009) : 366 4 Second Law of Thermodynamicsis the principle that the entropy of an isolated system may only increase or remain constant under time evolution from - Prigogine, I. The End of Certainty : Time, Chaos, and the New Laws of Nature (London: The Free Press, 1997): 205 5 Epstein, I.R. Showalter, K. “ Nonlinear Chemical Dynamics: Oscillations, Patterns, and Chaos.” The Journal of Physical Chemistry 100, no.31, (1996) : 13132 6 Epstein, I.R. Showalter, K. “ Nonlinear Chemical Dynamics: Oscillations, Patterns, and Chaos.” The Journal of Physical Chemistry 100, no.31, (1996) : 13132 7 Winfree, A.T. “The Prehistory of the Belousov-Zhabotinsky Oscillator” Journal of Chemical Education 61, no.8, (1984) : 662 8 Tyson, J. J. “What everyone Should Know About the Belousov-Zhabotinsky Reaction” Lecture Notes in Biomathematics 100, (1994) : 569
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BZ Reaction Diffusion Research
BZ Wave Propagation
BZ Chemicals The chemical solution has been prepared in the studio by a specific ratio between re-agents. The chemical wave propagation starts from the perturbation point and diffuse spherically.
A: sodium bromate, water, conc sulphuric acid B: sodium bromide, water C: malonic acid, water D: phenanthroline ferrous complex
BZ Solution Preparation AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
BZ Reaction Diffusion Wave Propagation 127
03 RESEARCH
Physarum and Belousov Zhabotinksy Reaction
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
129
03 RESEARCH
Digital Exploration/ Oregonator Model
Exploration II - Dr. Tetsuda Asai
The Oregonator code written by Dr. Tetsuya ASAI from the Graduate School of Information Science and Technology, Hokkaido University (Japan) has been extensively examined in the scientific article “Analog Reaction-Diffusion Chip Imitating Belousov-Zhabotinsky Reaction with Hardware Oregonator Model” (Int. Journ. of Unconventional Computing, Vol. 1, pp. 123–147, 2005). The CA-based code deals with local cell dynamics, whereas each cell arrayed on a 2D rectangular grid represents a processor computing with the Oregonator logic. The overall behaviour of the coupled identical cells is decided by the local chemically defined connection for diffusion and distance. Each cell represents the interactions between chemical species of u [i, j] and v[i, j], whereas [i,j] defines a specific point in space. The concentration of chemical species [ui, j], [vi, j] is represented by the values of system variables in each cell in the 2D space. In totality, the Bz is imitated by cells on a grid, while each cell representing an Oregonator/ oscillator.
Original values t=15
t=30
t=45
u= activator v= inhibitor a = excitability parameter; fixed point for excitation b = reaction parameter tau = reaction parameter du = diffusion coefficient dv = diffusion coefficient dt = time steps h = coupling distance of oscillators AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
t=60
t=75
u= 0.8 v= 0.1 a = 3.0 b = 0.02 tau = 0.01 du = 0.005 dv = 0 dt = 0.001 h =0.01
t= 90
t=105
t=15
t=30
t=45
t=60
t=75
t= 90
t=105
t=2
t=3
t=1
t=2
t= 3
t=4
U
u = 0.7
V
v= 0.5
dU
dU= 0.01
dt
dt= 0.002
h
h= 0.02 t=1
a
a = 2.0
b
b = 0.05
131
05 PRO(TO)CESSOR
Digital Exploration / Algorithm Expresses
Oregnator model The behaviour of the slime mould including the communicative and regulative mechanisms and thus the ability to survive are mathematically expressed with the Two Variable Oregonator model.
The equation describes how members of the entire “Physarum machine”, such as environmental and system-based (chemical) components, are interrelated mathematically and serve as systemic activators or inhibitors. The activator, the value u, equals the concentration of the cytoplasm at the propagating wave front. The inhibitor, the value v, is a combination of the following factors : rate of nutrient consumption, byproducts of chemical chains ignited by signals on photo- and chemoreceptor and concentrations of metabolites released by the plasmodium into substrate. The values u and v are based on a time scale by the parameter €. The parameter q scales the reaction rates and f is a stoichiometric coefficient. When varying coefficients of the Oregonator model are tested alternative behavioural trajectories and physical expressions are generated as expected. Changing coefficients are to be seen as data inputs of chemical nature, which cause perturbations to the nonlinear dynamic system. Visually, the Two Variable Oregonator Model describes the trajectory of the propagating wavefront and thus the morphological transformations. In our digital exploaration of the Two Variable Oregonator model, we mianly foucus on two different agrorithms. One is basiced on t’s model in terms of being adapting to a light-sensitive Belousov-Zhabotinsky (BZ) reaction with applied illumination. The other is from Tetsuya Asai, which is used to analog reaction-diffusion chip imitating Belousov-Zhabotinsky reaction.
Exploration I - Andrew Adamatzky The Oregonator code written by Prof Andrew Adamatzky from the International Centre of Unconventional Computation, University of West England (Bristol, UK) is very much targeted towards recording time lapse videos and image-snapshots of the propagating wavefront for imitating the Pseudopodia of the Slime mould. The propagating wave-front gets attracted to “Flakes” arranged in the chemical medium. The aim is to redraw the tubular connections between the attractors in order to imitate the slime mould logic of the shortest path, which is possible due to the mathematical analogy.
Du Du=0.4
Du=1.0
Du=1.6
Du=2.2
Du=2.6
Du=3.0
Dv=0.00
Dv=0.05
Dv=0.10
Dv=0.15
Dv=0.20
Dv=0.30
Dv AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
dx dx=0.15
dx=0.20
dx=0.25
dx=0.30
dx=0.35
dx=0.40
dt=0.001
dt=0.003
dt=0.005
dt=0.007
dt=0.008
dt=0.009
f = 0.0
f = 0.4
f = 0.8
f = 1.2
f = 1.6
f = 1.8
fi = 0.02
fi = 0.03
fi = 0.04
fi = 0.05
fi = 0.06
fi = 0.08
q=0.001
q=0.002
q=0.004
q=0.006
q=0.008
q=0.010
dt f fi q Du (u) = Wlocal concentrations of activator Dv (v) = local concentrations of inhibitor dt (Δt) = time step dx (Δx) = grid point spacing f = a stoichiometric coecient fi (Ø ) = sets up a ratio of time scale of variables u and v q = a scaling parameter depending on rates of activation/propagation and inhibition 133
03 RESEARCH
BZ Digital Catalogue / dt Variable
BZ Setup values >> f:1.0 ďŹ :0.05 q:0.0020 Du:1.0 Dv:0.0 dx:0.25 dt:0.012
BZ Values >> f:1.0 fi:0.05 q:0.0020 Du:1.0 Dv:0.0 dx:0.25 dt:0.012
Frame 0001 Frame 0100
Frame 0101 Frame 0200
Frame 0201 Frame 0300
Frame 0301 Frame 0400
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Frame 0701 Frame 0800
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Frame 0901 Frame 1000
Frame 1001 Frame 1100
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Frame 1201 Frame 1300
Frame 1301 Frame 1400
Frame 1401 Frame 1500
Frame 1501 Frame 1600
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Frame 1701 Frame 1800
Frame 1801 Frame 1900
Frame 1901 Frame 2000
Frame 2001 Frame 2100
Frame 2101 Frame 2200
Frame 2201 Frame 2300
Frame 2301 Frame 2400
Frame 2401 Frame 2500
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
BZ Setup values >> f:1.0 ďŹ :0.05 q:0.0020 Du:1.0 Dv:0.0 dx:0.25 dt:0.0020
BZ Values >> f:1.0 fi:0.05 q:0.0020 Du:1.0 Dv:0.0 dx:0.25 dt:0.020
Frame0100 0001 Frame
Frame0200 0101 Frame
Frame0300 0201 Frame
Frame0400 0301 Frame
Frame0500 0401 Frame
Frame0600 0501 Frame
Frame0700 0601 Frame
Frame0800 0701 Frame
Frame0900 0801 Frame
Frame1000 0901 Frame
Frame1100 1001 Frame
Frame1200 1101 Frame
Frame1300 1201 Frame
Frame1400 1301 Frame
Frame1500 1401 Frame
Frame1600 1501 Frame
Frame1700 1601 Frame
Frame1800 1701 Frame
Frame1900 1801 Frame
Frame2000 1901 Frame
Frame2100 2001 Frame
Frame2200 2101 Frame
Frame2300 2201 Frame
Frame2400 2301 Frame
Frame2500 2401 Frame
135
03 RESEARCH
BZ Digital Catalogue / du Variable
BZ Setup values >> f:1.0 ďŹ :0.05 q:0.0020 Du:0.6 Dv:0.0 dx:0.25 dt:0.0080
BZ Values >> f:1.0 fi:0.05 q:0.0020 Du:0.6 Dv:0.0 dx:0.25 dt:0.008
Frame 0001 Frame 0100
Frame 0101 Frame 0200
Frame 0201 Frame 0300
Frame 0301 Frame 0400
Frame 0401 Frame 0500
Frame 0501 Frame 0600
Frame 0601 Frame 0700
Frame 0701 Frame 0800
Frame 0801 Frame 0900
Frame 0901 Frame 1000
Frame 1001 Frame 1100
Frame 1101 Frame 1200
Frame 1201 Frame 1300
Frame 1301 Frame 1400
Frame 1401 Frame 1500
Frame 1501 Frame 1600
Frame 1601 Frame 1700
Frame 1701 Frame 1800
Frame 1801 Frame 1900
Frame 1901 Frame 2000
Frame 2001 Frame 2100
Frame 2101 Frame 2200
Frame 2201 Frame 2300
Frame 2301 Frame 2400
Frame 2401 Frame 2500
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
BZ Setup values >> f:1.0 ďŹ :0.05 q:0.0020 Du:1.8 Dv:0.0 dx:0.25 dt:0.0080
BZ Values >> f:1.0 fi:0.05 q:0.0020 Du:1.8 Dv:0.0 dx:0.25 dt:0.008
Frame0100 0001 Frame
Frame0200 0101 Frame
Frame0300 0201 Frame
Frame0400 0301 Frame
Frame0500 0401 Frame
Frame0600 0501 Frame
Frame0700 0601 Frame
Frame0800 0701 Frame
Frame0900 0801 Frame
Frame1000 0901 Frame
Frame1100 1001 Frame
Frame1200 1101 Frame
Frame1300 1201 Frame
Frame1400 1301 Frame
Frame1500 1401 Frame
Frame1600 1501 Frame
Frame1700 1601 Frame
Frame1800 1701 Frame
Frame1900 1801 Frame
Frame2000 1901 Frame
Frame2100 2001 Frame
Frame2200 2101 Frame
Frame2300 2201 Frame
Frame2400 2301 Frame
Frame2500 2401 Frame
137
03 RESEARCH
BZ Digital Catalogue / f Variable
BZ Setup values >> f:0.8 ďŹ :0.05 q:0.0020 Du:1.0 Dv:0.0 dx:0.25 dt:0.0080
BZ Values >> f:0.8 fi:0.05 q:0.0020 Du:1 Dv:0.0 dx:0.25 dt:0.008
Frame 0001 Frame 0100
Frame 0101 Frame 0200
Frame 0201 Frame 0300
Frame 0301 Frame 0400
Frame 0401 Frame 0500
Frame 0501 Frame 0600
Frame 0601 Frame 0700
Frame 0701 Frame 0800
Frame 0801 Frame 0900
Frame 0901 Frame 1000
Frame 1001 Frame 1100
Frame 1101 Frame 1200
Frame 1201 Frame 1300
Frame 1301 Frame 1400
Frame 1401 Frame 1500
Frame 1501 Frame 1600
Frame 1601 Frame 1700
Frame 1701 Frame 1800
Frame 1801 Frame 1900
Frame 1901 Frame 2000
Frame 2001 Frame 2100
Frame 2101 Frame 2200
Frame 2201 Frame 2300
Frame 2301 Frame 2400
Frame 2401 Frame 2500
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
BZ Setup values >> f:1.4 ďŹ :0.05 q:0.0020 Du:1.0 Dv:0.0 dx:0.25 dt:0.0080
BZ Values >> f:1.4 fi:0.05 q:0.0020 Du:1 Dv:0.0 dx:0.25 dt:0.008
Frame 0001 Frame 0100
Frame 0101 Frame 0200
Frame 0201 Frame 0300
Frame 0301 Frame 0400
Frame 0401 Frame 0500
Frame 0501 Frame 0600
Frame 0601 Frame 0700
Frame 0701 Frame 0800
Frame 0801 Frame 0900
Frame 0901 Frame 1000
Frame 1001 Frame 1100
Frame 1101 Frame 1200
Frame 1201 Frame 1300
Frame 1301 Frame 1400
Frame 1401 Frame 1500
Frame 1501 Frame 1600
Frame 1601 Frame 1700
Frame 1701 Frame 1800
Frame 1801 Frame 1900
Frame 1901 Frame 2000
Frame 2001 Frame 2100
Frame 2101 Frame 2200
Frame 2201 Frame 2300
Frame 2301 Frame 2400
Frame 2401 Frame 2500
139
03 RESEARCH
BZ Digital Catalogue / fi Variable
BZ Setup values >> f:1.0 ďŹ :0.02 q:0.0020 Du:1.0 Dv:0.0 dx:0.25 dt:0.0080
BZ Values >> f:1 fi:0.02 q:0.0020 Du:1 Dv:0.0 dx:0.25 dt:0.008
Frame 0001 Frame 0100
Frame 0101 Frame 0200
Frame 0201 Frame 0300
Frame 0301 Frame 0400
Frame 0401 Frame 0500
Frame 0501 Frame 0600
Frame 0601 Frame 0700
Frame 0701 Frame 0800
Frame 0801 Frame 0900
Frame 0901 Frame 1000
Frame 1001 Frame 1100
Frame 1101 Frame 1200
Frame 1201 Frame 1300
Frame 1301 Frame 1400
Frame 1401 Frame 1500
Frame 1501 Frame 1600
Frame 1601 Frame 1700
Frame 1701 Frame 1800
Frame 1801 Frame 1900
Frame 1901 Frame 2000
Frame 2001 Frame 2100
Frame 2101 Frame 2200
Frame 2201 Frame 2300
Frame 2301 Frame 2400
Frame 2401 Frame 2500
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
BZ Setup values >> f:1.0 ďŹ :0.03 q:0.0020 Du:1.0 Dv:0.0 dx:0.25 dt:0.0080
BZ Values >> f:1 fi:0.03 q:0.0020 Du:1 Dv:0.0 dx:0.25 dt:0.008
Frame0100 0001 Frame
Frame0200 0101 Frame
Frame0300 0201 Frame
Frame0400 0301 Frame
Frame0500 0401 Frame
Frame0600 0501 Frame
Frame0700 0601 Frame
Frame0800 0701 Frame
Frame0900 0801 Frame
Frame1000 0901 Frame
Frame1100 1001 Frame
Frame1200 1101 Frame
Frame1300 1201 Frame
Frame1400 1301 Frame
Frame1500 1401 Frame
Frame1600 1501 Frame
Frame1700 1601 Frame
Frame1800 1701 Frame
Frame1900 1801 Frame
Frame2000 1901 Frame
Frame2100 2001 Frame
Frame2200 2101 Frame
Frame2300 2201 Frame
Frame2400 2301 Frame
Frame2500 2401 Frame
141
03 RESEARCH
BZ Digital Catalogue / qVariable
BZ Setup values >> f:1.0 ďŹ :0.05 q:0.0020 Du:1.0 Dv:0.0 dx:0.25 dt:0.0080
BZ Values >> f:1 fi:0.05 q:0.0020 Du:1 Dv:0.0 dx:0.25 dt:0.008
Frame 0001 Frame 0100
Frame 0101 Frame 0200
Frame 0201 Frame 0300
Frame 0301 Frame 0400
Frame 0401 Frame 0500
Frame 0501 Frame 0600
Frame 0601 Frame 0700
Frame 0701 Frame 0800
Frame 0801 Frame 0900
Frame 0901 Frame 1000
Frame 1001 Frame 1100
Frame 1101 Frame 1200
Frame 1201 Frame 1300
Frame 1301 Frame 1400
Frame 1401 Frame 1500
Frame 1501 Frame 1600
Frame 1601 Frame 1700
Frame 1701 Frame 1800
Frame 1801 Frame 1900
Frame 1901 Frame 2000
Frame 2001 Frame 2100
Frame 2101 Frame 2200
Frame 2201 Frame 2300
Frame 2301 Frame 2400
Frame 2401 Frame 2500
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
BZ Setup values >> f:1.0 ďŹ :0.05 q:0.0060 Du:1.0 Dv:0.0 dx:0.25 dt:0.0080
BZ Values >> f:1 fi:0.05 q:0.0060 Du:1 Dv:0.0 dx:0.25 dt:0.008
Frame 0001 Frame 0100
Frame 0101 Frame 0200
Frame 0201 Frame 0300
Frame 0301 Frame 0400
Frame 0401 Frame 0500
Frame 0501 Frame 0600
Frame 0601 Frame 0700
Frame 0701 Frame 0800
Frame 0801 Frame 0900
Frame 0901 Frame 1000
Frame 1001 Frame 1100
Frame 1101 Frame 1200
Frame 1201 Frame 1300
Frame 1301 Frame 1400
Frame 1401 Frame 1500
Frame 1501 Frame 1600
Frame 1601 Frame 1700
Frame 1701 Frame 1800
Frame 1801 Frame 1900
Frame 1901 Frame 2000
Frame 2001 Frame 2100
Frame 2101 Frame 2200
Frame 2201 Frame 2300
Frame 2301 Frame 2400
Frame 2401 Frame 2500
143
03 RESEARCH
BZ Digital Catalogue / External Variable
BZ Setup values >> f:1.0 ďŹ :0.05 q:0.0020 Du:1.0 Dv:0.0 dx:0.25 dt:0.0080GD/999.9
BZ Values >> f:1 fi:0.05 q:0.0020 Du:1 Dv:0.0 dx:0.25 dt:0.008
Frame 0100 Frame 0001
Frame 0200 Frame 0101
Frame 0300 Frame 0201
Frame 0400 Frame 0301
Frame 0500 Frame 0401
Frame 0600 Frame 0501
Frame 0700 Frame 0601
Frame 0800 Frame 0701
Frame 0900 Frame 0801
Frame 1000 Frame 0901
Frame 1100 Frame 1001
Frame 1200 Frame 1101
Frame 1300 Frame 1201
Frame 1400 Frame 1301
Frame 1500 Frame 1401
Frame 1600 Frame 1501
Frame 1700 Frame 1601
Frame 1800 Frame 1701
Frame 1900 Frame 1801
Frame 2000 Frame 1901
Frame 2100 Frame 2001
Frame 2200 Frame 2101
Frame 2300 Frame 2201
Frame 2400 Frame 2301
Frame 2500 Frame 2401
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
BZ Setup values >> f:1.0 ďŹ :0.05 q:0.0020 Du:1.0 Dv:0.0 dx:0.25 dt:0.0080GD/999.999
BZ Values >> f:1 fi:0.05 q:0.0020 Du:1 Dv:0.0 dx:0.25 dt:0.008
Frame Frame0100 0001
Frame Frame0200 0101
Frame Frame0300 0201
Frame Frame0400 0301
Frame Frame0500 0401
Frame Frame0600 0501
Frame Frame0700 0601
Frame Frame0800 0701
Frame Frame0900 0801
Frame Frame1000 0901
Frame Frame1100 1001
Frame Frame1200 1101
Frame Frame1300 1201
Frame Frame1400 1301
Frame Frame1500 1401
Frame Frame1600 1501
Frame Frame1700 1601
Frame Frame1800 1701
Frame Frame1900 1801
Frame Frame2000 1901
Frame Frame2100 2001
Frame Frame2200 2101
Frame Frame2300 2201
Frame Frame2400 2301
Frame Frame2500 2401
145
03 RESEARCH
BZ Digital Catalogue / Wave Propagation Rules
BZ Setup values >> new_aperture
Aperture
Size
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Overlap
Medium Radius
BZ Setup values >> new_scales
Large Radius
Small Radius
Configuration
Irregular Configuration
Single Perturbation
Double Perturbation 147
03 RESEARCH
Material Research
Bioplastics are a type of plastics which can be made at home. As a source of material, vegetable strach, fats and oils, collagen and agar can be used instead of petroleum. Bioplastics derived from natural sources have similar properties with the petroleum based plastics which are typically converted into sheet for thermoforming. Forming the plastic with heat and giving it a final shape was a key factor for us to experiment the intelligence of the material. One of the most significant ability of the slime mold is reconfiguring itself under different environmental conditions and creating an intelligence with this collective behaviour. Through bioplastic experiments, we have sought for the ways either to embed an intelligence at the local level or to uncover the implicit intelligence to build up an architectural tectonic. In the studio we have experimented starch, agar and gelatin based plastics and tested their adaptibility tendency under different forces.
water
starch
vinegar
glycerin
Bioplastic | Ingredients | Wt 7 : St 1 : Vg 1/2 : Gy 3
1 Bioplastic | Ingredients | Wt 7 : St 1 : Vg 1/2 : Gy 3 AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
2
3
4
Bioplastic [Starch] # We have extensively tested biodegradable and editible bioplastics using different ingredients to achieve varied degrees of hardness, flexibility, and termoplastic properties. In general they were sensitive material, where the outcome varied according to the ingredients used, the temperatures in which they were subjected to, and the drying time. With changing some of these parameters, we have achieved to have some more ductile and jelly samples which might have a potential to apply the principle of communication of slime mold btw each nuclear and some more rigid samples which might create a strength to the building system. As a first step, we have done some ratio test with changing the proportion of glycerin and observed the shrinkage throughout the drying process. When we increased the ratio of the water, due to the fast evoporation, the shrinkage was increasing, too.
Ratio Tests | Day:01
Ratio Tests | Day:02 149
03 RESEARCH
Material Tests / Bioplastic
After ratio tests, we have experimented bioplastic using as a binding material which can create the elasticty to set the system re-configure itself. The test with paper balls showed us it is easy to keep the balls together and give them shape as a whole when the plastic is wet, however after model dries completely, bioplastic might turn into a stiff material depending on the ratio. Afterwards, we have tried to keep the bioplastic in an airtight balloon, to cease the drying period and keep it as an elastic material. Because plastic decrase the friction, the balls were allowed to reconfigure themselves at a certain level under forces.
Bioplastic | Paper Ball | Styrofoam
Bioplastic | Plastic Ball |Styrofoam | Balloon AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Bioplastic [Starch] # These are some samples that we have increased the strength of the material with changing the reinforcement. To reinforce it we have added some natural abaca fibers and paper balls into the plastic and observed the drying process. By having a non homogeneous plastic, it was easy to form the shape but not to control the shrinkage. We have also tried to reinforce the plastic with placing substances of different densities such as wood which is more stiff. Thereafter, to generate a bioplastic recipe which is stronger and stiffer, we have replaced the glycerin solution with %100 glycerin and multiple the starch ratio. With these tests, we have achieved to generate some pieces as strong as petroleum based plastics.
Bioplastic | Fiber | Paper Balls
Ratio Tests | Day:02 151
Bioplastic [Gelatin] #
We have used casted bioplastic into the plate like molds. After the first they have been removed from their molds, given a shell form and fixed on the foam The surface becomes a shell structure whichs is strong and stiff after drying. The material also becomes transparent
Bioplastic | Shell Structure
In this test, the different forms of molds are created and used to create bioplastic forms. At the first day, they are removed from their molds. When the shrinkage process gaining speed after first day, they were not in the mold and they gained their forms according to their mold shapes. Every time the curvateure of the mold gave a d’fferent stability to the dried biopastic.
Bioplastic | Different Curvatures AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
In this test, the same plate shape casted  with holes and without holes  and they are formed as a membrane using the tensile forces on it. The  surfaces behaves like a membrane before stretching and a shell after set completely.
Bioplastic | Streching
Here, bioplastic casted with patterns and without patterns as a plate shape. They fixed on the foam with pins to define the surface boundary conditions and the material inside the boundaries are free to move. The formation of pattern has decrased the duration of drying process and increased the tensile strenght of plate.
Bioplastic | Pattern 153
Bioplastic | Shell Structure
As a paralel study, we are also experimenting the structural capabilities of the biogel surface when it is completely rigid through forming it as a membrane using the tensile forces on it. To create bigger surfaces , we have tested joint systems to be able to assemble small pieces which are laser cutted to create a bigger surface. Yet, due to the changing environmental conditions, shrinkage is an issue to solve for larger structural principles.
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Bioplastic | Surface
As a paralel study, we are also experimenting the structural capabilities of the biogel surface when it is completely rigid through forming it as a membrane using the tensile forces on it. To create bigger surfaces , we have tested joint systems to be able to assemble small pieces which are laser cutted to create a bigger surface. Yet, due to the changing environmental conditions, shrinkage is an issue to solve for larger structural principles. 155
03 RESEARCH
Material Tests / information processing
We are exploring the influence of geometry and matter organization on the information flow and performance of the system. This research aspect examines, if chemical computation is architecture based or if architecture is the result of chemical computation. As the systems performance is based on the interaction of information and material data, we are exploring the chemical design of the material system. We are also looking at the scale of the design of our material system and the researching on the scale of matter reorganization.
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Three dimensional reaction diffusion The information processing within the material is based on 3D reaction diffusion. This can be observed as a spherically propagating wave within the electrical field in a volumetric environment. The plastic particles can be considered as “empty� voxels and the travelling ions, information and also a physical manifestation of reorganising matter.
157
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
159
03 RESEARCH
Material Tests / information processing
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
With the input of electricty the polymer engages in a redox reaction. Where there is subsequent expansion and contraction. One of the fundamental problems of utilising this type of polymer was their water content. However we have found a real-time fabrication methodology where the ANODE will be dehydrated quicker in comparison to its natural drying process and become a rigid area and the CATHODE will be able to draw and retain more hydration. The propagation of the field is unrelated to the geometry in which the reaction is contained in. This may also be a design opportunity of a prototype of non fixed form – where the geometry is the result of computation. However this does not refer to the absence of initial design set up with an architectural function in mind.
161
03 RESEARCH
Materiality/ Materialtests Monomers
Test 1 _Corn starch
Recipe
Test 2 _Potato starch
Recipe
Test 3 _Gelatine
Recipe
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
100 g Cornstarch, 200 ml water, 50 ml Glycerol, 10 ml vinegar
100 g Potatostarch, 200 ml water, 50 ml Glycerol, 10 ml vinegar
50 g Gelatine, 140 ml water, 1/4 tablespoon of glycerin
Shrinkage behaviour
Structural properties
Shrinkage behaviour
Structural properties
Shrinkage behaviour
Structural properties
83 % of original
83 % of original
83 % of original
no shape memory
moderate shape memory
very good shape memory
163
03 RESEARCH
Materiality/ Materialtests Co-polymers
Test 4_Agar Powder
Recipe
Test 5 _China Grass
Recipe
100 g Agar, 500 ml water, 100 ml Glycerol
50 g China grass, 500 ml water, 50 ml gycerol
Test 6 _Potato starch/ Agar Powder
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Recipe
50 g starch, 50 g powder agar, 300 ml water, 50 ml glycerol, 20 ml vinegar
Shrinkage behaviour
Structural properties
Shrinkage behaviour
Structural properties
Shrinkage behaviour
Structural properties
91% of original
91% of original
100 % of original
good shape memory/ compression strength
Moderate shape memory/ compression strength
Moderate shape memory/ compression strength 165
03 RESEARCH
Materiality/ Materialtests Co-polymers
Test 7_China Grass/ Potato Starch/ Glycerin
Recipe
Test 8_China Grass/ Potato Starch
Recipe
Test 9_Soy/ Cornstarch
Recipe
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
25 g Potato starch, 75 g China grass, 400 ml water, 50 ml glycerol, 10 ml vinegar
25 g Potato starch, 75 g China grass, 400 ml water, 10 ml vinegar
75 g cornstarch, 25 g soy, 200 ml water, 50 g glycerol, 10 ml vinegar
Shrinkage behaviour
Structural properties
Shrinkage behaviour
Structural properties
Shrinkage behaviour
Structural properties
91% of original
91% of original
91% of original
no shape memory/ compression strength
no shape memory/ compression strength
no shape memory/ compression strength 167
03 RESEARCH
Materiality/ Materialtests Co-polymers
Test 10_Potato Starch/ Agar Powder
Recipe
Test 11_Gelatine/ China Grass
Recipe
Test 12_Gelatine/ Agar Powder
Recipe
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
75 g Agar powder, 25 g potato starch, 500 ml water, 10 ml vinegar
25 g China grass, 25 g Gelatine, 300 + 70 ml water
25 g Agar powder, 25 g Gelatine, 150 + 70 ml water
Shrinkage behaviour
Structural properties
Shrinkage behaviour
Structural properties
Shrinkage behaviour
Structural properties
96 % of original
96 % of original
100% of original
no shape memory/ compression strength
very good shape memory/ compression strength
very good shape memory/ compression strength 169
03 RESEARCH
Slime mould & Cybernetics
Communication: Chemical signalling The nuclei are the brains of the slime mould and are encapsulated within a protective cellular membrane, which is endowed with receptors filtering chemical environmental information. The nuclei of the slime mould communicate via chemical signals such as the hormone cAMP. A scenario, where the communicative power is apparent, is when the population of individual amoebae faces the depletion of food sources and de¬hydration requiring the the organism to migrate for acquiring new food sources. In this case, a collective and collabora-tive cellular fusion is the key for survival, which is enabled by chemical signalling and sensing one another by the chemical se¬cretion of cAMP. While the amoebae move and aggregate towards the higher concentration of the signal, they release more chemical secrete for attracting more amoebae. The chemical signalling leads to the coordinated behaviour and movement of the individual amoebae forming a large commu¬nicative multinuclei amoeboid cell capable of migrating. After the fusion process, the chemical attractant breaks down due to chemical reactions. The fusion process is nonlinear and instable, as it is based on the interplay of the diffusive mobility of the amoe¬bae, the production of the attractant and the decay of the attractant. In the plasmodium stage, the communicative and regulative processes are initiated and regulated by a predefined set of chemical controllers such as chemicals, light and electric activity. As communication and regulation are based on chemical signals e.g. in form of hormones or chemical concentration levels, the envisioned chemical machine will be entirely chemically driven. This mode of communication makes physical attachment as seen in electric circuits superfluous, which allows for the constant rerouting of the flow of information and is the reason for the constantly changing physicality of the slime mould. In a synthetic system, whose internal and external communication is chemically
Fig.1: Communicating Nuclei
Fig.4: Chemical controllers: Nutrients
Salt
Fig.2: Communicating Nuclei
Fig.5:Chemical controllers: Salt
Fig.3: Controllers: Electricity
Fig.6: Controllers: Light
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Fig.7:Lack of nutrition: Verical growth led, the material design is one of the most crucial factors for the system to work.
Survival: Mechanisms for regulation and control
Fig.9: Gravitational field/ Lack Fig.10: Spreading body: high nutrition of nutrition
Fig.11: Growth on water
The purpose of directed and regulative mechanisms of information processing, which are of fundamental importance in biology, is the systemic survival through constant change and adaption. Together with the environment, the inputs, the desired outputs and the internal regulatory mechanisms the whole machine is formed. Therefore the performance of the slime mould automata is largely coupled to the outside world, as regulative processes are based on the chemical environmental and resulting systemic chemical messengers. Processes of regulation and decision-making are conducted in a strategically decentralized manner due to the absence of a (central) nervous system. The autocatalytic nature of the system and the decentralized control is responsible for the systemic stability and a key feature of dynamic systems. Within the slime mould, the regulative mechanisms of the system are expressed by changing morphologies enabled by the internal recycling of matter. Physical regulative expressions are closely connected to the oscillatory rhythms, whose generation is dependent on systemic chemical concentrations. Thus, the systemic morphology can be transformed and “controlled” by the setup and the chemical nature of the environment as mentioned above. These regulatory mechanisms include excitation waves, tree-like protoplasmic net¬works/ tubes and seemingly resting patterns. Excitation waves can be observed on a nutrient rich en¬vironment, whereas the slime mould distributes more “matter” in order to absorb more energy. Localized wave fragments and aggregated tree-like struc¬tures can be observed on a low-nutrient sub-strate, as less energy can be absorbed. Skeletal tree structures and material saving tubular connections between food sources can be observed on non-nutrient substrates. Thus the dynamic physical structure is highly task oriented. The physical regulative result is accompanied by a lot of noise evident by redundant networks which is rectified gradually and mathematically describable by Brownian motion. 171
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Feedback & Oscillation As the equation describes the whole systemic argument, it becomes clear that the aspect of feedback is not executed by an external observer, but is instead an interrelated systemic mechanism. Feedback between the innumerable nuclei, the communicating components of the system, is conducted via chemical signalling. Feedback, being a system-based chemical input has an impact on the frequency of the systemic oscillatory activity, which keeps the system away from equilibrium. Oscillation, besides being a form of inter-systemic feedback, is a method for global communication. Distinct oscillatory frequencies encoding messages are based on the nature of stimuli (chemo-attractants/-repulsions), which serve as per¬turbations to the excitable system of the slime mould. Thus, the oscillatory rhythm can be manipulated by altering the chemi¬cal gradients of an environment. This act equals changing variables of the Oregonator-algorithm. In physical tests, the increment in frequency of oscillatory rhythm happens in the event of an attractive stimulus and decreases, if the stimulus is repulsive. Physically, the frequency of os¬cillation is described within the slime mould by the protoplasmic streaming.
Information and measuring
Fig.12: Feedback and oscillation
Fig.13: Measuring systemic activity (electrically)
In general, external as well as internal information is of chemical nature. The systemic activity, which is physically exhibited by oscillating patterns, can be measured by electric activity. This systemic activity can be quantified and evaluated, whereas the sequence of systemic states in time equals information and can be translated into a message. Quantification enables generating a measurable common systemic language. The oscillatory activity equals the action potential of a brain, whereas the electric activity is chemically seen the oscillation of calcium ion concentrations. Fig.14: Physical memory: Tubes connecting nodes/ Scelotrium / Abandoned paths AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Memory and learning
Fig. 15: Anticipation
The occurrence of periodic events leads to anticipatory behavioural patterns, and thus memory, learning and behavioural changes are associated with a chemical change in matter. Anticipatory behaviour suggests, that information of past systemic states is stored and is accessible in the form of semi-permanent memory. A more physical interpretation of memory is the tubular connection between nodes, which are inactive structures. Abandoned white tubes are long term memory, whereas the slime mould doesn’t grow over these patterns anymore. Even the sclerotium phase can be seen as long term memory, preserving the genetic information of the system.
Chemical material properties and physical organization of the Physarum machine Fig.16: Section cellular wall/ chemical soup
Fig.17: Microscopic view of cellular wall/ membrane encapsulating the chemical soup
The main components of the heterogeneous mass are the ectoplasm tube, which is a gel membrane layer, enclos¬ing an endoplasmic core, the fluid state of the protoplasm. The external elastic cellular membrane consists to one half of glycoprotein, whereas the other half has a high carbohydrate to protein ratio suggesting the existence of proteoglycans. The internal protoplasm can be seen as an inhomogeneous chemical soup, which is composed of the following components: cyclic AMP (cAMP), calcium, phosphate, and other hosting chemicals. Together, they form the communicational channels. Considering the issue of the whole and the parts, the whole is formed by the membrane- encapsulating single cell, whereas the parts can be seen as the 1000s of nuclei responsible for communicative processes within the “chemical soup”. As matter is seen cyclic, the underspecified functional distinction between systemic components is supported by the fact that the physical structure of the single cell is composed of different material states. 173
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Nonlinearity: The Slime mould algorithm describes behavioural probabilities As mentioned, the behaviour of the slime mould and its ability to survive including the communicative and regulative mechanisms are mathematically expressed with the Two Variable Oregonator model. The fact that the Physarum machine follows a mathematical logic is a clear evidence for it being a computing device. The equation describes how members of the entire “Physarum machine”, such as environmental and system-based (chemical) components, are interrelated mathematically and serve as systemic activators or inhibitors. The activator, the value u, equals the concentration of the cytoplasm at the propagating wave front. The inhibitor, the value v, is a combination of the following factors : rate of nutrient consumption, byproducts of chemical chains ignited by signals on photo- and chemoreceptor and concentrations of metabolites released by the plasmodium into substrate. The values u and v are based on a time scale by the parameter €. The parameter q scales the reaction rates and f is a stoichiometric coefficient. When varying coefficients of the Oregonator model are tested alternative behavioural trajectories and physical expressions are generated as expected. Changing coefficients are to be seen as data inputs of chemical nature, which cause perturbations to the non¬linear dynamic system. Visually, the Two Variable Oregonator Model describes the trajectory of the propagating wavefront and thus the morphological transformations. -algorithm with explaining coefficients This algorithm can also describe the autocatalytic Belousov Zhabotinsky Reaction . The Belousov-Zhabotinsky Reaction is a chemical reaction which is a causal model for complex biological systems. Despite the difference in ‘constitution and composition’ comparative to its biological archetype the reaction successfully produces phenomenological similarities. The BelousovZhabotinsky reaction demonstrates behaviours that are difficult to translate into digital computation due to its complex interplay of travelling local rules that respond to a larger scale global rule within a non-hierarchical system. This reaction has proliferated in the field of material sciences where this chemical reaction is directly applied. The significance of this is the subtraction of exterior control of the material physicality, and the reaction itself is inherent in the material substance which becomes a fundamental constituent of the resultant behaviour. The mathematical model also indicates the high systemic sensitivity turning the slime mould into a statistical machine. Due to that, two identical tests can have different behavioural trajectories accompanied by probabilistic transformations, whereas long term behaviour is in general unpredictable. Due to the high sensitivity, computation of the regulatory mechanisms doesn’t even halt in the absence of data inputs. This could be an indication on the existence of inter-systemic feedback. AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
-diagram of slime mould logic/ recursive state graph as a systemic design reference The patterning of the BZ reaction demonstrates a system of coupled feedback loops, a machinic system that internally regulate itself to selfperpetuate, and also “prevent any one phase of the process from being carried to a catastrophic extreme.” In biology feedback loops are often observed in communication and internal self-regulatory processes (of cells), and occurs at indiscriminate levels of scale. The BZ reaction is comparable to many natural phenomenas such as the cAMP signalling of the cellular slime mould where the produced cAMP signal propagates across the field, which in time diffuses to nothing and the cyclic process perpetuates. The BZ reaction have forced chemical kinetics to think about the self-organization of chemical reaction in time and space. For mathematicians and physicists, it is an ideal example of complex behaviour of nonlinear dynamical systems : limit cycle oscillations, bistability and hysteresis. The underlying mathematical similarity between BZ reaction and these biological examples means that the reaction can serve as a simple chemical model of the invariably more complicated biological systems. Especially experiments that would be impossible or impractical in the biological setting can often be performed with ease in the BZ reaction. The limited capabilities of the conventional digital mode of simulation is now beginning to be recognised, and this open the possibilities of a direct jump from chemical computation to material actuation. There has already been attempts mainly in Japan and the US to directly materialise BZ reaction behaviours into ‘self-oscillating polymer gels’, which are amorphous gels that engages in some characteristic behaviours of living organisms. “Polymeric hydrogels that exhibit autonomous, coupled chemical and mechanical oscillations are a unique example of synthetic, active soft matter.”
Fig.18: Sequences of Slime mould information processing Activator u: Concentration of the cytoplasm at the propagating wave front
â‚Ź: Time scale
Fig.19: Sequences of a Belousov- Zhabotinsky Reaction Inhibitor v: -Rate of nutrient consumption -Byproducts of chemical chains ignited by signals on photo- and chemoreceptor -Concentrations of metabolites released by the plasmodium into substrate
q: scales the reaction
f: Stoichiometric coefficient
Fig.20: Oregonator model BZ-reaction/ Slime mould
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Ross Ashby_ Homeostat (1948) Ross Asbhy’s “Homestat” (1948) was to developed as a regulatory device comparable to and inspired by human body parts and characteristics. The Homeostasis is based on delicate biological mechanisms, which perform compensatory/ regulatory mechanism when slight changes in e.g. temperature or chemical states are detected. The behavioural purpose of the machine is to preserve a systemic condition equalling a dynamic stability/ equilibrium, as this systemic state is crucial for basic functionalities of the organism to be carried out. Design-wise, the architecture of the Homeostat is made of several electronic circuits interconnected by static wiring, which was inspired by the reflex areas in the spinal cord of any animal. Therefore, the idea of connecting restricted number of components “[...] in order to discover that independence could be achieved with the smallest number of elements connected in a system providing the greatest number of possible interconnections” became increasingly important to Ashby. The fixed nature of communication is the reason behind the inability for developing memory, learning or data storage. Thus, performative aspects seem to be missing, whereas the purposeful systems of control and communication emphasis is on executing specified goals. “ Indeed, one could argue that for Ashby there is no analogy: the brain, like the homeostat, is simply a material switching device, connected through sensors and effectuators with the forces of the environment.” p.46 This deterministic approach to adaptive behaviour can be seen as a contrast to dynamical systems theory. The corrective feedback, attempting to mimic compensatory actions of humans/ animals in order to overcome systemic differences, in the Homestat is represented by an interconnected electromagnetic circuit, which stabilizes through adaptive interconnection of systemic components. Thus the brain and the environment are embedded within one system as an entity, as they are in one feedback loop. However, from the 1950’s onwards, he proves that self-organization is mathematically possible.
Fig.23: Ashby, Ross. 1948. Homeostat with four units.
Fig.24: Ashby, Ross. 1948. Homeostat with four units. AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Fig.25 Ashby, Ross. 1948. Homeostat wiring diagram 177
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William Grey Walter_Tortoise (1948/ 1949) W. Grey Walter, being a neurophysiologist, extensively studied and measured the cyclic brain activity and electric oscillatory patterns (wavelength and rhythm), which then became the language of his model of the cybernetic brain. “He also developed a method of measuring what is called the readiness potential in human subjects, which permits an observer to predict a subject’s response about a half to one second before the subject is aware of any intention to act.” p.47 By analyzing the localized alpha activity of the brain, he extensively contributed to radar technology. The tortoises called Elmar and Elsie can be considered as simple animals, which were constructed of three wheels, two motors for steering and motive power, light and bump censor, an electronic circuit, two batteries and a plastic shell. These interconnected mechanical components produces complex and unpredictable behaviours. Furthermore these systems are designed to have free will, uncertainty and independence.
Fig.26: Walter, Walter Grey. 1949. Tortoise.
The “brains” endowed with sensors, initially scan their environment in search for light as a stimuli and systemic input. The resulting systemic behaviour, based on a predetermined vocabulary, depend on reconnecting electric circuits and on flow of electricity. “ Walter’s brain science did not emulate physics, say, in exploring the properties of the fundamental units of the brain (neurons or their electromechanical analogues); instead it aimed to show that when simple units were interconnected in a certain way, their aggregate performance had a certain character (being capable to adapt to the unknown).” p.49 As the regulatory systemic members are combined in a deterministic and static manner, whereas the body-plan is essentially based on an electric circuit. Consequently, the learning capability is limited, whereas physically implemented memory- circuits represent learning. Later models of the “Tortoise”, were endowed with “[...] memory circuits in which associations are stored as electric oscillations [...]”. As the behaviour of the physical automata is based on the possibility of interconnecting systemic components in multiple ways, the algorithm describing the Tortoise considers probability and the statistical nature of the machine. These facts make the Machina Speculatrix an important precedent for robotics.
Fig.27: Walter, Grey Walter. 1949. Tortoise and light stimuli. AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Fig.28: Compartmentalized human brain
Fig.29: Walter, Walter Grey. Brain activity: Different electric patterns in different brain compartments.
Fig.30: Walter, Grey Walter: 1949. Bodyplan Tortoise. 179
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Gordon Pask_Chemical Computer The setup of Gordon Pask’s “Chemical Computer” (1950/1960) is a first step to architecture-free computing. The setup foresees an array of threads, which are represented by vertically hanging electrodes dipped into a dish with ferrous sulphate solution. When a current is passed through the electrodes and a high current density occurs, dendrite branches grow at the ends of the electrodes. The branches degenerate and dissolve, if the current reaches below a critical level. Within this open ended search process, endless material configurations are possible. As Pickering points out, this architecture -free computer “[...] grew without any painstaking design, exploiting the liveliness of matter instead[...].”. The lacking specification enables modification of “[...] their systemic interconnections as they grow in order to improve proficiency at calculation or pattern recognition. [...] Once a thread was broken it would spontaneously rebuild and reconfigure itself [...].” . Therefore it is “ [...] capable of interacting with the world independently of its designer.” . Abandoning the idea of “machines with goals” and adopting the idea architecture-less computers was already an apparent development initiated with Pask’s “Chemical Computer”. Within Pask’s “Chemical Computer” the idea of memory is attached to the generation of matter, which is expressed by the capability of a broken thread to repair itself by reproducing the same path. Pask’s chemical computer cannot be described by an algorithm, as according to him algorithmic systemic logics are not the defining aspect of cybernetics. The Chemical Computer physically embodies a constant search for open ended possibilities in terms of material configurations, which is expressed by an evolving and emerging systemic physicality resulting from chemical reactions. This is also the reason why there is no feedback loop designed. The systemic robustness lies in the ability to self repair and matter reconfiguration. The fact that external control is being abandoned, makes the system autonomous.
Fig. 31: Dendrite growth for electrochemical computation
Gordon Pask’s approach to (second order) cybernetics is however relevant for current architectural issues. Considering the growing field of ubiquitous computing, a shared environment and synthetic ecology consisting of inhabitants, spaces for inhabitation and devices could merge into a mutually constructive coexistence. His approach also suggests to develop an architecture, where the inhabitant and the inhabitable space evolve as part of this constructive relationship.
Fig. 32: Pask, Gordon. 1950/60. Growing and dissolving matter in Chemical Computer. AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Fig.33: Pask, Gordon. 1950/60. Setup Chemical Computer.
"The reasoning behind Pask’s interest in underspecified goals is that if a designer specifies all parts of a design and hence all behaviours that the constituent parts can conceivably have at the beginning, then the eventual identity and functioning of that design will be limited by what the designer can predict. It is therefore closed to novelty and can only respond to preconceptions that were explicitly or implicitly built into it." p.58 Fig. 34: Pask, Gordon. 1950/60. Path regeneration is memory. "Some of the design principles embodied in Pask's device are: 1) construction, reconstruction and repair of its own parts (structural closure) 2) proliferation of alternative connected structures through branching, dendritic structural forms (increasing structural variety), 3) reward to useful structures in the form of material (i.e. current & iron) to build more structure (economic allocation of resources), 4) dynamic stabilization and de-stabilization of functional structures (performancecontingent survival) 5) finite amount of building resources (zero-sum competition and recycling of materials) 6) ill-defined structural elements (structural autonomy vis-a-vis the designer) 7) openness of structures to perturbations in their external environments (informationally open)." p.6
“Once a thread was broken it would spontaneously rebuild and reconfigure itself, with the break moving up the course of the thread. A sensor electrode was inserted into the thread in order to measure the output waveform generated by this arrangement." p.58 181
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Building automation systems Input Sensors are responsible for sensing & filtering of information, which equals environmental encoded energy. This ability is crucial for a systemic decisionmaking process. The system should not be able to receive external signals and thus systemic inputs at every stage of conversion.
Information processing The amplifier translated signal for actuator. Information is encoded by electric currents, which can be potentially read in the binary language (0,1/ on, off). This information contains a systemic message, which gets translated into physical/ mechanical behaviour. Thus the aspect of systemic information processing constantly translates a message into new systemic expressions and mechanisms. Measuring the information of these mechanisms is a way of controlling the uncorrupted information flow. The electrically encoded information is transported by electronic semiconductors. This fact requires a specific systemic material properties.
Output: The output behaviour needs to be connected to the reference signal. Usually a systemic response lags behind the stimulus, whereas a certain degree of inertia can be useful.
Fig. 35: Design of a Control System, automatated loop control system Second order cybernetics
Feedback The output signal is compared with the desired state, wheras this value/ state is contained within the reference system. Furtermore, the (instable) reference signal is crucial for the system to avoid equilibrium. To ensure inequilibrium, a constant feedback resulting from this comparative act and the resulting readjustment of the system is AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
required. The feedback is the result of the comparative reference signal comparing input and output. The feedback or “error� signal characterizes the quality of the systemic output.
Thermostat Electronically driven systems with hard wiring strongly depend on manual and deliberate rituals performed by the observer by the means of e.g. a thermostat. A thermostat, being a temperature sensing and regulating component of a control system, is responsible for maintaining the system’s desired temperature value on a constant level by comparing it to the systems actual value. It is the only regulative component allowing manual human intervention into the regulative mechanisms of heating, cooling or air conditioning systems with the aim of saving energy. By rotating the control valve, simple physical (hydraulic) principles are activated, which regulate the hot water flow from the boiler to the heating in order to achieve the desired room temperature. During this process, the fluid enclosed in the control valve gradually heats up and expands as it is a sensory element. Due to this the corrugated pipe is compressed resulting in the valve gear being pushed downwards, which cuts off the flow of hot water to the heating and equals the valve being closed. When the room temperature gradually falls, which can be seen as a systemic disturbance and a discrepancy from the desired value, the valve gear automatically shifts upwards again allowing hot water to flow through the heating. The expanding liquid performs tasks of measuring and evaluation. This sensitive self-regulating mechanism allows for a constant room temperature, if viewed over a long period.
Fig. 36: Thermostat 183
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References Adamatzky, Andrew. Physarum machines : computers from slime mould. New Jersey : World Scientific Publishing, 2010. Adamatzky, Andrew, Ben De Lacy Costello and Tetsuya Asai. “Universal Computation with Limited Resources: Belousov-Zhabotinsky and Physarum Computers.” International journal of bifurcation and chaos in applied sciences and engineering. VOL 18; NUMB 8 (2008). Adamatzky, Andrew and Jeff Jones. “Programmable reconfiguration of Physarum machines.” Natural Computing Volume 9, 2009, Number 1, 21923. Adamatzky, Andrew and Jeff Jones. On Electrical Correlates of Physarum Polycephalum spatial activity: Can we see Physarum machine in the dark? Biophysical Reviews and Letters 6 (2011) 29-57. Cariani, Peter. “To Evolve an Ear: Epistemological Implications of Gordon Pask’s Electrochemical Devices”. Systems Research, 10(3), (1993) : 1933. Hickey, D S, and L A Noriega. “Insights into Information Processing by the Single Cell Slime Mold Physarum Polycephalum.” control2008org (2008) : 565-569. Gorecki, Jerzy and Gorecka Joanna. “Chemical programming in reaction diffusion systems”. Proceedings of the 2005 Workshop on Unconventional Computing: From Cellular Automata to Wetware. Beckington: Luniver Press (2005): 1-13. Haque, Usman, “The architectural relevance of Gordon Pask”. 4d Social - Interactive Design Environments, Architectural Design. London: Wiley & Sons (2007): 54-61. Johnston, John. Allure of Machinic Life: Cybernetics, Artificial Life, and the New AI. Cambridge, MA : MIT Press, 2008. Lytton, William W.. From computer to brain: Foundations of computational neuroscience. Berlin ; London : Springer, 2002. Mallgrave, Harry Francis. The architect’s brain : neuroscience, creativity, and architecture. Chichester : Wiley-Blackwell, 2010. Matsumaru, Naoki, Florian Centler and Peter Dittrich. “Chemical Organization Theory as a Theoretical Base for Chemical Computing”. Proceedings of the 2005 Workshop on Unconventional Computing: From Cellular Automata to Wetware. Beckington: Luniver Press (2005): 75-88. Nakagaki, Toshiyuki et al. “Obtaining multiple separate food sources: behavioural intelligence in the Physarum plasmodium.” Proceedings of the Royal Society B Biological Sciences 271.1554 (2004) : 2305-2310. Pask, Gordon. “A Comment, a case history, a plan”. Reichardt, Jasia ed., Cybernetics, art and ideas. London: Studio Vista (1971): 76–99. Pask, Gordon. Approach to cybernetics. London : Hutchinson, 1961. Pickering, Andrew. The Cybernetic Brain: Sketches in Another Future. Chicago ; London : Chicago University Press, 2010. Tsuda, Soichiro and Jeff Jones.The emergence of synchronization behavior in Physarum polycephalum and its particle approximation. Biosystems. Volume 103, Issue 3, March 2011, Pages 331–341. Tsuda, Soichiro, Masashi Aono, and Yukio-Pegio Gunji. “Robust and emergent Physarum logical-computing.” Biosystems 73.1 (2004) : 45-55. AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Walter, Walter Grey. The Living Brain. London : Duckworth, 1953. Walter, Walter Grey. “Studies on Activity of the Brain”. Cybernetics: circular casual, and feedback mechanisms in biological and social systems. New York, NY (1953) : 689-696. Walter, Walter Grey. “An imitation of life”. Scientific American, 182(5), (1950): 42-45.
Image credits Fig. 2: http://quizlet.com/6331453/biology-131-lab-midterm-1-flash-cards/ Fig. 13:Adamatzky, Andrew and Jeff Jones. On Electrical Correlates of Physarum Polycephalum spatial activity: Can we see Physarum machine in the dark? Biophysical Reviews and Letters 6 (2011), p.4, p.14. Fig.15:Saigusa, Tetsu et al. “Amoebae anticipate periodic events.” Physical Review Letters 100.1 (2008), p.018101-2. Fig.16: Tero, Atsushi, Ryo Kobayashi, and Toshiyuki Nakagaki. “A mathematical model for adaptive transport network in path finding by true slime mold.”. p.4. Fig.17: http://lloydsnlondon.wordpress.com/2010/03/12/physarum-material-internet/ Fig.18: http://www.youtube.com/watch?v=l6kyE_cct-0 (images extracted from video) Fig.19: Adamatzky, Andrew, Ben De Lacy Costello and Tetsuya Asai. Reaction-diffusion computers. Amsterdam ; Oxford : Elsevier, 2005, page 125. Fig.20: Adamatzky, Andrew. Physarum machines : computers from slime mould. p.56. Fig.23: Pickering, Andrew. The Cybernetic Brain: Sketches in Another Future. Chicago ; London : Chicago University Press, 2010, page 337. Fig.24: Fig. 25: Ashby, Ross. Design for a brain, The origin of adaptive behaviour. London: Chapman & Haal, 1952, page 102. Fig. 26: Johnston, John. Allure of Machinic Life: Cybernetics, Artificial Life, and the New AI. Cambridge, MA : MIT Press, 2008, page 42. Fig. 27:Walter, Walter Grey. “An imitation of life”. Scientific American, 182(5), (1950): 42. Fig. 28: Walter, Walter Grey. The Living Brain. London : Duckworth, 1953, page 17.Fig. 29: Fig. 30: Walter, Walter Grey. The Living Brain. page 200. Fig. 31: http://paskpresent.com/exhibition/?page_id=26 Fig.32: Pickering, Andrew. The Cybernetic Brain: Sketches in Another Future. Chicago ; London : Chicago University Press, 2010, page 338. Fig.33: Pickering, Andrew. The Cybernetic Brain: Sketches in Another Future. Chicago ; London : Chicago University Press, 2010, page 337. Fig.34: Pask, Gordon. Approach to cybernetics. London : Hutchinson, 1961, page 106. Fig.36: http://greengopost.com/honeywell-opower-join-forces-for-smart-thermostat/ http://wn.com/thermostat
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04 PHASE 覺襤1 PROTOTYPE _Materiality _Algorithm _Design of The System _Architectural Functions _Integration-Disintegration
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Materiality | Feedback Based Material Systems
Conductive Bioplastics
In order to alter the inherent composition of the bioplastics we have opted for adding metal oxides into the mix. This allowed the plastics to conduct electricity in varying degrees relative to its other ingredients and its ratio. We are changing the chemical composition of the material in order for it to conduct ( electricity in this case ) – but the main aim is for them to conduct different types of data.
Preparation
In order to alter the inherent composition of the bioplastics we have opted for adding metal oxides into the mix. This allowed the plastics to conduct electricity in varying degrees relative to its other ingredients and its ratio. We are changing the chemical composition of the material in order for it to conduct ( electricity in this case ) – but the main aim is for them to conduct different tyes of data.
Wirirng Without Wires
The propagation of colouration on the sheet of agar is the result of the oxidation of the metal pieces embedded into the bioplastic. This colouration is also a visual indication of the area that is ‘conductive’, hence LEDs can be lit when they come in contact with their corresponding charges. Also slight repulsion among the same poles were also visible.
Conductive Bioplastic // Colouration on the Positive Pole
Wiring Without Wires Through Material AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
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Prototypical Material Exploration
The Reasons for Laboratory Architecture/ Fabrication - Although there is no need for high technology fabrication, there is PRECISION in the manufacturing processes that is currently lacking in the generic construction industry -The materials involved are ‘cleaner’ resources in comparison to concrete, steel and glass, and the base materials can also be extracted from renewable sources. - Producing bioplastics are also non- toxic procedure without waste in production - and can also be reduced to almost nothing at the end of its lifecycle
Preparation of the mould
Hot water bath of mixed ingredients
Injection moulding
Air curing and refrigeration
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Gel state for injection
Components to Units
MgSO4
AGAR
C3H8O3
GELATINE
Ingredients For Bioplastic - PLant Based Degradable Polymers
a component
a unit ( 4 components )
a cluster ( 8 - 10 units )
weight: 6g price*: 1.4 p
weight: 24g price*: 5.6 p
* Price based on materials consumed to manufacture
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BZ Reaction
Belousov- Zhabotinsky Reaction
Reaction diffusion patterns: The BZ reaction behaviour is rich and complex to the degree where there are limitations in explaining them in the context of digital simulations. This is another facet of the BZ reaction, where despite its relative simplicity of its chemical set up, the presence of several concurrent reactions makes it a challenge in its duplication outside the chemical medium. This difficulty is partly due to travelling local reactions that is also effected by a larger global rule. This does not mean a vertical hierarchy within the system, but rather a coupling of several reactions of different orders, where the word ‘order’ takes on the definition of a disposition in relation to others of equal preference. The limited capabilities of the conventional digital mode of simulation is now beginning to be recognised, and this open the possibilities of a direct jump from chemical computation to material actuation.
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Spherical Propagation of Currents in Components
Digital simulation of material behaviour according to electrical field conditions. 193
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Generative Code Principles | Algorithm
Design of Particle With Sensory Features
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
The generalmorphology of an agent and its basic underlying algorithm is illustrated in the figures. An agent occupies a single discrete location in the environ-ment, corresponding to a single pixel of a digitized image. Each agent is typically initialized at a randomly chosen unoccupied and habitable location and with a random orientation (from 0 to 360 deg, freeing the agent from the restrictive architecture of the underlying discrete image). The agent receives chemotactic sensory stimuli from its environment (chemoattractant levels stored in the trail map) via three forward ensors, and the agent responds to differences in the local environment chemoattractant levels by altering its orientation angle by rotating left or right about its current position. This code has been used to develop an initial setup for the arrangement of components which will start the chemical computation. Particle based code has been converted into a component based 3D model configuration within the platform of Softimage-ICE.
Data Map
Trail Map
stores problem dataset and agentpositions
stores diffusing food source stimuli and agent trails
Configuration Data Projection
Agent Autocrine Sensory / Deposition Behaviour
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Generative Code Results | 3D Slime Mold Logic
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
The initial setup is based on 3d slime mold logic code that we have developed seeks for attraction points in which particles are aggrageting in a specific period of time. This shows how matter organization habe been developed according to environmental information. Total particle number is changing ragarding to need of the user and each time we run the code we get different results according to the temporary attractive point which serves for different performances of the system.
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Generative Code Principles | Initial Setup Generation
The arrangement of the clusters and the setup is decisive for the system’s computational and communicational potential . This is the global way of preprogramming the perfomance of the system. The global preprogramming is also based on the types of connections between individual components: touching, wires, binding material (components of cybernetic system). Therefore an architectural setup composed of discrete geometry is needed for the global computational capacity and the continuous adaption of form. The site specific chemical gradients lset on the site according to the user needs and site information. Matter organisation is based on the environmental information and the logic of generative design tool which is 3D slime mold logic.
Environment defined by site specific chemical gradients
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Population of particles depending on user needs
Environmental information is extracted and translated into matter organisation
The initial setup of the system is attached to a chemical battery in order to generate the electric field. The initial incomplete field, is completed by the inhabitant by repositioning mobile poles.
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Design of The System
Cybernetic system The design of the system is based on cybernetic control systems of second order with nested sub-systems, whereas the inhabitant is the observer of the system. The obserer is capable of understanding and evaluating the chemical phenomena of the system. Members of a conventional control system such as transducers, actuators and sensors are defined by materials and specifically designed material properties. Furthermore, the designed cybernetic system engages in parallel processesing of information and feedback making it autonomous.
Cybernetic Building System
Feedback Inactive system
Building Automation Systems COUNTER EXAMPLE Control system
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Control mechanism: User ritual
Electroluminesence
Electrical Thermostat
Fixed Lighting
Moisture release/ Discolouration Chemical
Expansion/ Shrinkage
Full Circuit
Physical
Electrical
Mechanical Ventilation
Fixed wiring
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Chunk Section_A
Bioplastic Component
Biogel Binding Agent
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Building chunk section shows different performances of the system happening on different networks of the system. Different activities caused by of an external trigger occurs through a temporary electric field which has been translated into electrochemical processes. The internal electric activity of the initial setup which provides the electric servicing of the building initiates the electrocluminisescent lighting networks. The electric current leads to moisture which generates cooling system and physical deformations which generates openings for ventilation . Different clusters aggregates into a structure which creates the physical space. Different types of connections bw each cluster creates the possibility of computing matter through a defined initial setup which is capable of information processing. Biogel which is the binding agent of the aggregation creates the flexibility to the system to respond electrochemical processes.
Life Cycle of The System
We are proposing a life cycle model which starts with lab fabrication concept which allows chemical precision and reduces the fabrication waste, and followed by an assamblage on site with no site waste and minimized labor due to refabrication and establishes a system based on information processing which can be described cybernetic computer computing. After usage, due to infomation processing level, the system disintegrates itself facilitating by reducing temprorary and redundant parts. Considering the cybernetic scenario of an ecology, which is striving for cooperative survival, a chemically computing material system based on biopolymers is appropriate due to the biocompatibility and their responsiveness to e.g. human activity and metabolic processes. Considering the designable behavioural capacity, material is beyond being an interface. As systemically needed, material allows chemical sensitivity and when a material arrangement is of purposeful nature, polymers with non-linear phase transitions embedded within a feedback based system are imaginable. A project specific definition on lab architecture is necessary. As polymer material fabricated in laboratories is usually small scale, speculation about the large scale fabrication methodology and application is required. Aspects we can borrow from are the highly precise lab-based fabrication methods and the means of constantly examining material regarding specific parameters. The knowledge gained serves as feedback to the improve the microarchitecture of the polymer. This idea of pre-programming and inheritance probably defines this thesis take on lab architecture. Material needs to be developed and tested regarding its performance scientifically in a laboratory, but the amount of material needed cannot befabricated in a regular lab environment. 203
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Chunk Section_B
Moisture Release / Cooling
Electroluminescence Lightning System
Metal Oxidation / Wiring up
Bioplastic Components + Biogel Binding Agent
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
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Architectural Functions
Ph Lightning Through Material Conductivity
Cooling Through Water Release AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
E
hysical Deformation Due to Electrical Activity
Electric Networks on BUilding Material
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Integration-Disintegration
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
The network of components starts integrating and expanding through chemical reactions which differentiate a whole network than others. If information is no longer processed by the system, the components of the systems start disintegrating. The disintegration process eliminates every trace of existence of the system and lefts no remaining building waste, as biodegradable building completely disintegrates biologically and chemically. The prototypical scenario becomes crucial for the deployment of the system in a context that we need to deal with changing needs due to rapid technological changes and demolition waste problems .
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Information Processing Network
The network of components starts integrating and expanding through chemical reactions which differentiate a whole network than others. If information is no longer processed by the system, the components of the systems start disintegrating.
The initial chemical reaction is the excitation of electroluminescent ions in conjunction with the electric activity. The electroluminescence not only visually expresses information processing, but is a secondary signalling system as well. The visual signalling system immediately expresses the adaption of the system’s behaviour and the chemically changing nature of matter. The electric activity signals the activity of the system in relation to the user.
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_Definition _Theory _Mode of Operation _Design and Materiality _Physical Simulation _Glossary
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Definition
The Chemical Machine Chemical agencies-Processor- Environment The chemically self-contained machine is comprised of the environment, chemical agencies such as the inhabitant, microorganisms, plants, environmental chemicals and the processor. It is a form of life, as it is based on intracellular communication, signalling and self-regulation. The systemic members are bound together by a dynamic chemical interdependency, which is critical for the existence of the entire Machine and its members. As all systemic members rely on mutual mechanisms of information processing and self-regulation, the distinction between the inanimate and animate world is overcome and the chemical coupling allows a more collaborative rather than oppositional or hierarchical relationship between the two distinct worlds. The rituals of inhabitation and the human lifecycle are given by the operational nature of the machine. While the processor needs the disturbances given by the chemical agencies in order to avoid the state of equilibrium, the chemical agencies need to be provided with oxygen and light in order to survive. These mutual activities of selfregulation conclude in the cooperative act of survival forming an adaptive cybernetic environmental entity. The Chemical Machine is inherently sensitive to external stimuli light and carbon dioxide. If this information deviates from predefined values, localized perturbations within the Chemical Machine take place leading to emergent circuiting ( communication) and self-regulating (computation). Considering the life-supporting goals of the Chemical Machine, equilibrium equalling systemic death is strictly to be avoided. Given by the underlying statistical mathematical model, the system is highly sensitive to external chemical disturbances and inter-systemic changing concentration ratios. The Chemical Machine, being based on the interplay of chemical agencies, does not require an observer as per second order cybernetics responsible for judging the success of regulatory mechanisms. As the previously defined chemical agencies are of equal importance and impact, the Chemical Machine is essentially a non-human centric system. The Chemical Machine is of polyscalar nature. The design starts from the chemical scale, whereas the global scale is non-foreseeable, but is critical for communicating the sense of an ecosystem.
Food-Oxygen
Waste CO2
Chemical Agency
1. Self-regulating autonomous system 2. Environmentally driven 3.Chemical control 4.Output is input and feedback to system
The Chemical Machine AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
CHEMICAL MACHINE Macroenvironment Heat Substrate Water Light
Ch e m i c a l Agency
Light
CO2 Perturbation
Oxygen Perturbation
Microenvironment
Humidity - Heat -CO2 Perturbation
Heat-Light - Oxygen - Morphological Adaption Self-regulation
Processor
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Situating The Chemical Machine
Cybernetics: From deterministic architecture - free computation
to
In order to situate the work within the field of cybernetics, an evaluation on relevant early cybernetic experiments and theories of this Second World War technology, has been conducted. As attempted by Ashby’s “Homestat” and W. Grey Walter’s “Tortoise”, the Chemical Machine is not intending to mimic biological regulatory mechanisms mechanically or electrically. An example for a deterministic cybernetic model, which is inspired by the reflex areas in the spinal cord of any animal, is Ashby’s Homeostat. The deterministic architecture of the Homeostat is made of several electronic circuits interconnected by static wiring granting communication of fixed nature. Within this model developing memory, learning or data storage is impossible. As performative aspects seem to be missing, the emphasis is on purposeful systems of control and communication for executing specified goals. “ Indeed, one could argue that for Ashby there is no analogy: the brain, like the homeostat, is simply a material switching device, connected through sensors and effectuators with the forces of the environment.” 35 A cybernetic model displaying the context between design and systemic purpose is W. Gray Walter’s Tortoise. These simple animals were constructed of three wheels, two motors for steering and motive power, light and bump censor, an electronic circuit, two batteries and a plastic shell. Interconnecting the mechanical components produces complex and unpredictable behaviours, whereas these systems are designed to have free will, uncertainty and independence. “In Grey Walter’s model of the brain, in other words, agency is fully embodied in a material set of parts and connections. Yet what is missing from this account is the necessary emphasis on the complexity of these connections. For it is precisely this complexity of connection that makes ‘‘a handful of inert components’’ yield behaviour that is interesting in itself. “36 Considering the historic developments of cybernetic models, there has been a tendency of overcoming the fixed circuit designs and deterministic brainlike control-system , as these designs are merely able to express imitative behaviour. Another projective tendency is the development from electromechanical to digital to chemical machines. These developments including temporary and emergent circuiting has been tested within Pask’s approach to cybernetics. Thus, the Paskian Chemical Computer (1950/1960) has been an important theoretical model for analysis, even though it is working without a mathematical model and essentially is a machine without goals. However, within Pask’s Chemical Computer, important ideas on architecture free computation were expressed by an unstable and unconstrained assembly of synthetic components such as a setup of an array of vertically hanging electrodes dipped into a dish with ferrous sulphate solution. These were capable of producing organic behaviours in their self-organized interplay. When a current is passed through the electrodes and a high current density occurs, dendrite branches grow AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Verner Panton (1960), Junior Chair by Vitra [http://www.instyle.com/instyle/package/holidaytrends/ photos/0,,20063741_20153721_20362525,00.html]
IBM PC, 1981 [http://pc-museum.com/officewing.htm]
Homeostat, 1948 [Pickering, Andrew. The Cybernetic Brain: Sketches in Another Future. Chicago ; London : Chicago University Press, 2010, page 337. ]
at the ends of the electrodes. The branches degenerate and dissolve, if the current reaches below a critical level. Within this open ended search process, endless material configurations are possible. As Pickering points out, this architecture -free computer “[...] grew without any painstaking design, exploiting the liveliness of matter instead[...].”. 37
Computer science: Chemical Computers
BZ Gels [Chen, I. et al. “Shape- and Size-dependent patterns in self-oscillating polymer gels” Soft Matter 7, no.7, (2011)}
Reaction Diffusion Processor [Adamatzky, Andrew, Ben De Lacy Costello and Tetsuya Asai. Reaction-diffusion computers. Amsterdam ; Oxford : Elsevier, 2005, page 48. ]
“Roots”, Roman Kirschner (2005/ 2006) [http://paskpresent.com/images/romankir.jpg]
In recent times, chemical processors operating with the logic of the Two Variable Oregonator Model, namely the Belousov Zhabotinsky Reaction, have gained the interest of experimentally working computer scientists. This aspect is crucial, as computational mechanisms of the slime mould can be retraced chemically serving an inanimate technology. Interestingly, the development on the field of chemical computation has been supported by the aspect of systemic failures due to a fixity and multiplicity of systemic components in digital computers. Conventional hard wired computers are fragile, as damaging one component usually brings the entire system to halt. Chemical computers are self healing as their physical matter can be constantly recycled. Furthermore, Reaction-diffusion processors have a high fault tolerance and are capable of automatic reconfiguration unlike digital computers. Chemical processors based on non linear chemical reactions are capable of parallel executed computational mechanisms and error correcting. Due to these parallels, the developments in the realm of non-linear chemical computation and specifically Reaction-Diffusion Processors are beneficial beyond the field of computation. The limitations however include the 2 dimensional nature of BZ-processors or even their scale and materiality. Furthermore, the Chemical Machine needs to go beyond the mathematically analogue slime mould or BZ-processors in terms of performance.
Material sciences: Plastics/ Polymers
The development within the field of stimuli responsive polymers as well as BZ gels is a critical factor for this thesis. There have been attempts to materialize the BZ reaction previously, so that chemical computation becomes a base for material actuation, which exhibits behaviours of living organisms. These materials operate autonomously without external deliberate control. The behaviour of the BZ gels is however limited to volumetric fluctuations only.
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Physarum and Belousov Zhabotinksy Reaction
Besides the changing colour of in vitro solution, another method to observe the reaction is as a thin film. Goodwin explains the BZ reaction as a biological model of a field - an excitable media in which the cells “interact with one another in time (their kinetics) and in space their relational order: how the state of one region depends upon the state of neighbouring regions). These two properties together define a field.” The reaction demonstrates two ‘topologically distinctive wave patterns’ , expanding concentric waves and the rotating scroll. “The rings slowly travel outwards from centres that arise spontaneously throughout the dish, with new circles forming at regular intervals. Each pattern retains its original form up to the boundary established by two colliding waves, which then annihilate one another.” On the surface of the solution patterns observable in nature and variations of the Turing pattern emerges. These patterns are manifested as a result of several operations running simultaneously- reaction and diffusion. This results in a system in which the concentrations of reactants and products oscillate temporally and spatially and in which this oscillation can result in ordered patterns.
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
What appears in the BZ reaction is not only important for their appearances; these waves are visual manifestations of the travelling local reactions and its refractory period within excitable media that is comparable to examples in nature not visible to the naked eye ( ie. Intercellular level). The propagating waves are comparable to the cyclic refractory period of amoebae and the slime mould during their repetitive signal releasing communication or the recovery time for BZ reaction reagents to prepare for their next re-excitation. “ A single chemical reaction, with sufficiently nonlinear kinetics, can exhibit a remarkable variety of dynamical behaviour. It is natural to ask whether coupling together two or more oscillating or similarly complex reactions might lead to a still richer phenomenology. ” The patterning of the BZ reaction demonstrates a system of coupled feedback loops, a machinic system that internally regulate itself to self-perpetuate, and also “prevent any one phase of the process from being carried to a catastrophic extreme.” In biology feedback loops are often observed in communication and internal self-regulatory processes (of cells), and occurs at indiscriminate levels of scale. The dynamic behaviour manifested by an autonomous selfregulatory process is a close analogy to Piaget’s definition of transformation and self-regulation of structure. 219
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Physarum and Belousov Zhabotinksy Reaction
The BZ reaction behaviour is rich and complex to the degree where there are limitations in explaining them in the context of digital simulations. This is another facet of the BZ reaction, where despite its relative simplicity of its chemical set up, the presence of several concurrent reactions makes it a challenge in its duplication outside the chemical medium. “The fundamental difficulty in simulating excitable media is the separation of spatio-temporal scales in such systems. The time scale on which variables change as the system becomes locally excited is typically several orders of magnitude faster than the time scale on which interesting behaviour occurs in the extended medium.” AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
This difficulty is partly due to travelling local reactions that is also effected by a larger global rule. This does not mean a vertical hierarchy within the system, but rather a coupling of several reactions of different orders; where the word ‘order’ takes on the definition of a disposition in relation to others of equal preference. The Oregonator is a simplified mathematical model of the Belousov - Zhabotinsky chemical reaction, where it can also be applied to describe the propagating wave pattern of the Physarum.
The waves generated by the digital simulation of the oregonator model is shown transposed on top of Physarum.
The Oregonator Equation:
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Physarum and Belousov Zhabotinksy Reaction
Diagram of Belousov - Zhabotinsky Reaction cycle in order of chemical progression.
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Belousov - Zhabotinsky Chemical Reaction procedure Recipe: A. 25gm sodium bromate, 335ml water to dissolve, then 10ml conc sulphuric acid. B. 10g sodium bromide, water to 100ml C. 10g malonic acid, water to 100ml D. 1, 10 phenanthroline ferrous complex (Fisons, Loughborough) Malonic acid is oxidised by bromate, producing carbon dioxide, but in acid soluÂŹtion the reaction cannot proceed; there must be a latent period while the CO2 diffuses away. The solution is ‘poised’; foci of blue appear randomly, and spread as circles. New foci appear at circle centres, so that a series of bulls-eyes (not spirals) progresses. Add 6ml of solution A to the glass beaker, then add 0.5ml of B, then quickly mix in 1ml of C. Leave the brown mixture to lose bromine (by an open window) until it is pale straw colour or colourless (2-3 minutes if agitated or if in a flat dish). Add 1ml of the redox indicator D, mix thoroughly and pour into a 9cm glass or plastic petri, on a white (illuminated) background. It will turn patchy blue, then clear to a brown-red. Foci of blue will appear (sometimes one must wait 5 minutes!) and progress as expanding rings whose centres produce oscillating foci. Different foci, even in the same dish, may have very different periods. The pattern complicates for some 25 minutes at 20 degrees, or the dish can be shaken to restore homogeneity. The solution turns blue, then red again, then new foci appear at indeterminate times and places and the process repeats.
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Belousov Zhabotinksy Reaction
Walking BZ gel : Diagram of Belousov - Zhabotinsky Reaction cycle patterning in hydrogel ( MIT) walking do to expansion and [Chen, I. et al. “Shape- and Size-dependent patterns in self-oscillating polymer gels” Soft Matter 7, no.7, (2011)] contraction [Yoshida, R. “Self-Oscillating Gel as Novel Biomimetic Materials” Journal of Controlled Release 140, no.3, (2009)] The limited capabilities of the conventional digital mode of simulation is now beginning to be recognised, and this open the possibilities of a direct jump from chemical computation to material actuation. There has already been attempts mainly in Japan and the US to directly materialise BZ reaction behaviours into ‘self-oscillating polymer gels’, which are amorphous gels that engages in some characteristic behaviours of living organisms. “Polymeric hydrogels that exhibit autonomous, coupled chemical and mechanical oscillations are a unique example of synthetic, active soft matter.” Hydrogels in BZ reaction solution ( without the ferroin indicator) AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Diagram of Belousov - Zhabotinsky Reaction cycle
Diagram of Belousov - Zhabotinsky Reaction cycle: U value cycle highlighted
U + V value in flux . ( graph from Processing ): U value in RED 225
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BZ Digital Catalogues | Expansion/Shrinkage
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Mode of Operation
Computation for the sake of self-regulation The Chemical Machine is utilizing principles of Reaction Diffusion Computing and in specific the BZ-processors for computational purposes. Computation and information processing is based on the sequential BZ chemical reaction and mathematically follows the cyclic and Oregonator logic, which links the biological model of the slime mould to the autocatalytic chemical BZreaction. The purpose of the synthetic regulatory mechanisms is essentially to serve the cooperative act of survival and specifically to regulate the oxygen, hydration and light level of the microenvironment and if applicable the macroenvironment. For the inhabitants as well as the potentially incorporated biological life, the Chemical Machine provides water, air, protection from drastic climate changes, food and light for plants and microorganisms to conduct photosynthesis. The Chemical Machine is capable of computing the required light level e.g. necessary for conducting photosynthesis. The Chemical Machine is capable of regulating the oxygen level as well, which is controlled by the degree of membrane pore opening for the release of stored oxygen resulting from swelling and de-swelling sub-processors. The regulatory mechanisms are cyclic in nature and are expressed by physical material behaviours such as swelling and de-swelling of subprocessors and chemical precipitation. As the same sub-processors also illuminate by chemo-luminescence, a functionally underspecified view on matter is required. However, a highly specific chemical pre-programming of the sub-processors along with their setup equalling the architecture of the computer is essential.
Selfregulation of light AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Oregonator cycle
Communication: Chemical signalling For the regulatory chemical mechanisms to take place communication within the chemical machine is essential. For communicative processes to take place purposefully, the system filters relevant information regarding light and Oxygen level, which are found within the inhabitant as well as in the environment. As per definition, communication is the transfer of encoded data. In the case of the Chemical Machine, the propagating wave of the BZ medium is responsible for transferring a message, which is encoded by concentration profiles. The propagating wave is an inter-systemic signal causing localized excitations of interconnected sub-processor. A sub-processor is susceptible to chemical signals only if it is not in the refractory period. This process of excitation leads to emergent chemical circuiting equalling changing concentration profiles of interconnected sub-processors. The capability to send and receive inter-systemic signals helps avoiding the state of equilibrium. An architectural system capable of communicating on chemical signals has certain implications as hard wired electric circuits for signal delivery and the functional distinction between inert matter and information processing networks becomes obsolete. Transient chemical circuits among the sub-processors evolve, when the wave-front starts propagating between the sub-processors. This communication allows passing on information by influencing the concentration ratio of neighbouring sub-processor. This form of chemical signalling doesn’t require specified positions for input and output, a fixed body-plan for “transmitting� a signal or any electric input. On a more global scale, the interconnection of functionally independent Chemical Machines allows a chemically led communication among these entities. In this way, behavioural and systemic states can be passed on to neighbouring processors as information and a form of input. The information can contain indications on environmental conditions as well as conditions of the neighbouring inhabitants transmitted via material states of the synthetic system. In this way, the goal of cooperative survival results in a mode of inhabitation. Systemic activities of self-regulation are not seen on an individual but on a Can receive signal
Inactive
cooperative level. The communicative power saves the array of Chemical Machines from equilibrium, as processors are constantly receiving chemical signals from neighbouring processors.
Emergent chemical circuits
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Mode of Operation/ Emergent circuiting
Spherical hydrogels with BZ reaction reagents transferring waves between themselves : timelapse sequence AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
BZ gels being prepared in BZ reaction solution 241
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Mode of Operation
Chemical control Electronically driven systems with hard wiring strongly depend on manual and deliberate rituals performed by the observer by the means of e.g. a thermostat. A thermostat, being a temperature sensing and regulating component of a control system, is responsible for maintaining the system’s desired temperature value on a constant level by comparing it to the systems actual value. It is the only regulative component allowing manual human intervention into the regulative mechanisms of heating, cooling or air conditioning systems with the aim of saving energy. By rotating the control valve, simple physical (hydraulic) principles are activated, which regulate the hot water flow from the boiler to the heating in order to achieve the desired room temperature. During this process, the fluid enclosed in the control valve gradually heats up and expands as it is a sensory element. Due to this the corrugated pipe is compressed resulting in the valve gear being pushed downwards, which cuts off the flow of hot water to the heating and equals the valve being closed. When the room temperature gradually falls, which can be seen as a systemic disturbance and a discrepancy from the desired value, the valve gear automatically shifts upwards again allowing hot water to flow through the heating. The expanding liquid performs tasks of measuring and evaluation. This sensitive self-regulating mechanism allows for a constant room temperature, if viewed over a long period. As the goal of a thermostat is to preserve dynamic equilibrium, a critical analysis of Ross Asbhy’s “Homestat” (1948) is appropriate. The “Homeostat” was developed as a regulatory device comparable to and inspired by human body parts. Homeostasis is based on delicate biological
Standard Digital Simulation ( no environmental input )
mechanisms, which perform regulatory mechanism when slight changes in e.g. temperature or chemical states are detected. The ritual and the mechanisms are suitable as well as appropriate for a mechanically working system based on physical principles. Therefore, the thermostat is not a conceptually and technically valid regulatory device for the Chemical Machine based on the computing BZ-Medium, as it does not require an active human regulatory ritual. This is given by the systemic sensitivity and excitability in the case of changing light and oxygen levels. In this way, the Chemical Machine is based on mutual control based on activation and inhibition. A deliberate and repetitive regulative ritual also implies the desire to preserve homeostatic conditions, which are technically non-existent in a non-linear dynamic system mathematically based on the Two Variable Oregonator Model.
Black Box and a reference system As the mechanisms of self-regulation cannot be observed on the chemical scale, the system equals a black box. Despite of their inaccessibility, the physically and chemically expressed regulatory results of the inanimate Chemical Machine are crucial for the inhabitants’ survival and are an immediate sign for a successful information processing. Additionally, a reference system enabling the comparison of systemic states does not exist in the classical sense, but due to the cyclic occurrence of chemical states are cyclic the system itself serves as a reference system. Furthermore, resulting physical changes in the array of processors due to chemical mechanisms should be explicit to the naked eye.
Analogue environmental input to digital simulation
Chemical control AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Feedback Feedback has the purpose to regulate the performance of a task in case it differs from the desired output of a goal oriented machine. The feedback within the Chemical Machine works without deliberate human intervention and is not conceptualized as a corrective input. The Chemical Machine based on the Oregonator Model is dependent on negative feedback initiated by the inhibitor. Without feedback through oscillation, being a sign for high sensitivity, the Chemical Machine would reach the state of equilibrium very soon. Given by the systemic mathematical model, feedback is an essential systemically interlinked component demanding excitability. Feedback does not serve preserving a (homeo-) static condition, which would equal static chemical concentrations. Chemical precipitations resulting from regulatory mechanisms are capable of productively disturbing the systemic chemical concentrations. Thus, a precipitate can be considered as another form of inter-systemic feedback and an input. An example for a system based on corrective feedback is Ashby’s “Homeostat”, which attempts to mimic compensatory actions of humans/ animals in order to overcome systemic differences for preserving a dynamic equilibrium. Stabilization is achieved by adaptively interconnecting systemic components of the electromagnetic circuit. In this way the “brain” and regulatory systemic actions equalling feedback are embedded within one system as an entity, which is similarly envisioned within the chemically computing machine. Chemical Agency: Inhabitant
Excitation
Emergent circuiting
Oxygen Input
Oxygen Output
CO2 Perturbation
Opening and closing of surface pores enables gas exchange
Change in pH and Morphological adaption
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Mode of Operation
Intersystemic language and Measuring: pH pH is an indicator by in which the system of Belousov - zhabotinsky reagents within the subprocessors regulate the spatial volume and ultimately dimension. The fluctuation in the ph is the chemical mechanism behind the swelling and the deswelling of the actual building fabric. The hydrogels expand in alkaline environment and they contract in acidic. Hypercells is a system where the building matter emcompasses a chemical regulator that is sensitive to constantly fluctuating ambient chemical levels as well as the intended manipulation / perturbation of the chemical system. Information processing and messaging techniques not necessarily need to be based on electronics, as it is just one of many ways of coding. In order to monitor, whether self-regulation is successfully taking place, measurable data gained needs to be evaluated. The specifically developed measuring concept relies on pH values can be quantified and measured in time.
Alkaline
Visualisation of changing pH value
pH- Values with interrelated behaviours AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Acidic
Oscillating pH values/ activators and inhibitors [https://spie.org/x47370.xml?ArticleID=x47370]
Data storage Data storage, on a general note, creates memory in a system and if a systemic behaviour changes due to this data storage, it can be considered learning. Considering the computational logic of the BZprocessor, data storage is based on concentrations profiles of reagents. The notion of data storage, even if it is of ephemeral nature, becomes relevant in context with the self-regulation of space and volume. This condition needs to be preserved for a longer period and is expressed by coupled material behaviours, as preserving concentration profiles is not feasible within the Chemical Machine. A physically expressed self regulatory result is to be seen as systemic memory. As memory and matter are constantly recycled, there can be nothing like permanent chemical memory. Permanent chemical memory are also not useful in context with the systemic goal of self-regulation and adaption.
Morphological Self-regulation Morphological self-regulation is expressed by the gradual, time delayed and reversible swelling and de-swelling of sub-processors. The presence of carbon-dioxide( acidic) leads to the shrinkage of subprocessors resulting in spaces and volumes expanding. If spaces are inhabited by oxygen releasing agents such as plants, spatial volumes shrink, which is due to the expansion of sub-processors in context with alkaline pH-values. Morphological aspects of self-regulation can also influence spatial subdivisions as well as the closure or opening of passages and channels depending on the frequency and intensity of utilization by the chemical agencies. As this may lead to spaces uninhabitable by people, the non-human centric nature of the Chemical Machine becomes apparent. Morphological self-regulation, depending on material behaviour, cannot be correlated to existing building tectonic functions. By self-regulation in architecture the surface to volume ratio can be improved globally and locally, as space and volume adapt in accordance to occupancy rate. It becomes a purposeful semi-permanent form adaption to a specific environmental chemical condition or a chemically unique agency. Due to the reversibility of self-regulation, the past of a system such as the interaction with a previous user are inaccessible to current inhabitants.
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Design/ Sub-Processor
Hydrogel beads hydrated with water
Design of a sub-processor Each chemically independent sub-processor computes with the Oregonator logic and can be considered as the CPU of the Chemical Machine, where cycles per second describe the computational power of each component. The need to compartmentalize the computing engine of the Chemical Machine into subprocessing units is critical for sustaining the propagating wave. Digital and physical studies have shown, that spherical geometries of the components correspond most suitably with the geometrical nature of the propagating wave. Considering examinations on the productivity of sub-processors, the most successful scale of each component is 20 mm diameter. In terms of materiality, each sub-processor is made of silicone-hydrogel enabling reversibility for morphological aspects of self-regulation. Hydrogel bead absorbing bz solution AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Decision of The Geometry
For the desicion of the geometry for a sub-for a subprocessor we have digitally tested the behaviour of differnet type of geometries. While spherical geometries allow more efficient and homogenious wave propagation, rectangular ones have limited directionalities.
Materiality BZ reagents absorbed hydrogel
sensitive to pH and light (with luminescent indicator) - hydrogel absosrbent polymer - reagents: Sodium Bromate Sulfuric Acid Tris(bipyridine)ruthenium(II) chloride (Ru(bpy)3Cl2) Malonic Acid Ferroin
As the ratio of systemic inhibitors and activators (u/v ratio), can be correlated to specific pH-values, behavioural states are designed in accordance to pH-values. While pH-values in the acidic range cause shrinkage of the subprocessor, the subprocessor swells within the alkaline range. Within the Chemical Machine Prototype for Mars, there is one type of sub-processor, which is both sensitive to light and carbon-dioxide at the same time. The required chemical sensitivity of the subprocessor can be specifically pre-programmed by the choice of reagents engaging in the BZreaction and need to be chosen in consideration with the specific scenario and interrelated environmental necessities. Besides enabling chemical sensitivity, a even higher behavioural control can be achieved by embedding thresholds for e.g. excitability.
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Hydrogels in BZ reaction solution
Hydrogels in BZ reaction solution AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Preparing a few hydrogels for BZ reaction
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Design/ Exploration_Array of Sub-Processors
Sub-processors attached by channels
Sub-processors attached in linear modules AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Sub-processors attached by triangular modules
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Design/ Exploration_Array of Sub-Processors
Fixed connection
Degree of freedom: 2
Degree of freedom: 3
Elastic connection
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Clustered connections: elastic and fixed
Linear connection: Elastic and fixed
Linear strings: Twisting for clustering
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Design/ Exploration_Array of Sub-Processors
Linear strings: Twisting for clustering
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Design/ Exploration_Array of Sub-Processors: Twisting
Setup_ 1st order of logic Sequence of subprocessor types Angle/ Interface
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Setup_2nd order of logic Twist
Setup_2nd order of logic Degree of rotation_angle
Degree of curvature: Implications for the wave propagation
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Design/ Exploration_Array of Sub-Processors: Braiding
Overlap Interval = 4
Overlap Interval = 3
Overlap Interval = 2
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Design/ Array of Sub-Processors: Maximum Neighbours
Silica gel in BZ solution
Silica gel in BZ solution AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Array of sub-processors: Maximum Neighbours The arrangement of sub-processors needs to consider inter-systemic needs for communication, wave transmission and eventually self-regulation. The arrangement logic follows the idea of maximum neighbours for ensuring that each sub-processor is capable of receiving inputs from neighbouring processors. The arrangement logic of maximum neighbours allows a nonlinear and non-deterministic propagation of the wave and probability in terms of spatio-temporal distributed information processing and self-regulation.
Hydrogels in pressurised environment hexagonally packing
Hydrogels in pressurised environment hexagonally packing + air subprocessors 261
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Design/ Scale & Productivity
Sub-processor scale and productivity
For processing 11 g of CO2/ min
In order to meet performative necessities of the Chemical Machine, which are given by the specific scenario, the computational rate of three subprocessor scales has been analysed. These represent the product within a given timespan. Larger sub-processors have a higher rate, as it can hold on to more information with the same time-span and have a higher area of influence. Larger sub-processors can not be replaced by volumetrically equivalent smaller sub-processors, as there is a higher inefficiency factor. Therefore, the computationally necessary number of sub-processors is decisive for the mass. Considering that the productivity of the sub-processors is linked to the scale, physical implications are the inevitable result.
10 mm
Decreasing Productivity
20 mm
14_ 20 mm 5 mm
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
145_ 10 mm
1344_5mm
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Rate of computation: Speed of wave propagation AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
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Design/ Scale & Productivity
Rate of computation: Efficiency of wave propagation AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
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Design/ Prototypical Processor
Component arrangement model 1
Component arrangement model 2 AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Spherical components larger than the silicone cast size inserted: deformation
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Design | Thickness and productivity
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Digital studies have shown that systemic productivity is related to the strategic distribution of matter. The communicating and self-regulative capacity of the system increases with an increasing number of independently computing sub-processor. Considering this fact, 99% of the total number of subprocessors have been designated for self-regulative tasks of the Mars environment (see calculations).
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Design/ Geometry and organization of space
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AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
The fact that a spherical geometry is beneficial for each sub-processor for sustaining the propagating wave, applies to the scale of space as well. A propagating wave hitting a sharp edge dissipates. Another critical fact, which was identified on the scale of sub-processors, applies to the scale of space is the rule of maximum neighbours. Both rules have architectural implications, as the processor could spatially be composed of spherical and cellular spaces.
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Design/ Membrane_Pores
Hydrogel cast on silicone surface
Hydrogel cast on silicone surface AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Hydrogel cast on silicone surface
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Design/ Membrane_Pores
Perforation cast on silicone sheet
Different densities of perforations AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Silicone sheet cast : not all are hollow
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Design/ Prototypical detail
Locally, the organization depends on the computing subprocessors, which are embedded within a self-healing and ph-sensitive Membrane. Biological vessels engage in oxygen production. The exterior of the processor is build by a porous membrane allowing data exchange with the environment. In general the organizational structure and the operation of the system are interlinked.
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Subprocessors
CPU Allow morphological and environmental selfregulation by mechanical oscillation and emission of light
Interior Membrane with Pores -Allows sensing of carbondioxide -allows moisture exchange with microenvironment
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Design/ Prototypical detail
Silicone and hydrogel sphere cast 2
Silicone and hydrogel sphere cast 2 AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
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Physically Simulating the chemical machine : light
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Chemical Machine v.02 Setup Diagram
Physically Simulating the Chemical Machine: This is a physical simulation of how the proposed hydrogels with BZ reagents would behave. For Hypercells we have placed greater focus on the prototype which emulate the projected behaviour of the system rather than making a physical model which is static and representational. In the final prorotype the sensors inside the hydrogel model are linked to the coefficients of the oregonator script ( the digital simulation of BZ and slime mold) which: 1.allocates different lengths of brightness of lights and 2. controls the different speed of rotation of servo motors that control the syringes to change the pH levels of the hydrogles which swell and contract at different pH levels. - which in loop affects the sensor values linked to the oregonator script. AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
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Reaction A
Reaction B Reaction A and Reaction B are exactly the same code running in processing, the only difference is that Reaction A has no environmental input in a complete digital platform - there is no noise in its operation. Reaction B has the the same algorithm however the coefficients of the equations are linked to the sensors embedded within the silicone prototype. According to time, general light condition and the physicality of the silicone model the physical world feeds fluctuating values into the algorithm, resulting in patterns of unforseeable variation.
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Morphological self-regulation is expressed by the gradual, time delayed and reversible swelling and de-swelling of sub-processors. The presence of carbon-dioxide( acidic) leads to the shrinkage of subprocessors resulting in spaces and volumes expanding. If spaces are inhabited by oxygen releasing agents such as plants, spatial volumes shrink, which is due to the expansion of sub-processors in context with alkaline pH-values. Morphological aspects of self-regulation can also influence spatial subdivisions as well as the closure or opening of passages and channels depending on the frequency and intensity of utilization by the chemical agencies. As this may lead to spaces uninhabitable by people, the non-human centric nature of the Chemical Machine becomes apparent.
Photocell sensors manipulating the script - and the script lighting the LEDS LEDS manipulating the photocell sensors - loop
Digital simulation where the variables are fed by the real time environment. 289
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Chemical Machine v.01
Initial attempts of the Chemical Machine simulating light.
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
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Chemical Machine v.01
Development of Prototype Initial stages
Sensor and LEDS connected to the oregonator script Different pH levels controlling different servos and the speed of its rotation.
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Chemical Machine v.01 Setup Diagram Physical Setup: volumetric fluctuations according to pH changes.
BZ chemical reaction
pH probe : MICROCONTROLLER measure osciallation of pH
Syringes: To emulate the oscillatory pH changes of BZ reaction to material / physical setup.
The chemical Belouzov Zhabotinsky reaction running the sero motors that push the syringe to change the pH of Hydrogels.
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Chemical Machine v.01
Oscillation of the Oregonator script in the digital platform - There is absolutely no noise in the system. It is a fully insulated and simulated environement in which the oregonator equation is calculated
The pH reading of the Belouzov- Zhabotinsky reaction over period of 10 minutes. Extreme fluctation and osciallatory behaviour is recorded.
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
The pH sensor in Belouzov- Zhabotinsky reaction solution
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Chemical Machine v.01
Hydrogel with pH indicator
Hydrogel with different regions of ph indicated Swelling at the alkaline pH and contraction at the acidic pH is observed
Hydrogel with an unexpected cracking
Hydrogel after prolonged period of time within the Belouzov Zhabotinsky Reaction solution.
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Hydrogel after prolonged period of time within the Belouzov Zhabotinsky Reaction solution - Timelapse Sequence 297
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Chemical Machine v.01
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Morphological self-regulation, depending on material behaviour, cannot be correlated to existing building tectonic functions. By self-regulation in architecture the surface to volume ratio can be improved globally and locally, as space and volume adapt in accordance to occupancy rate. It becomes a purposeful semi-permanent form adaption to a specific environmental chemical condition or a chemically unique agency. Due to the reversibility of self-regulation, the past of a system such as the interaction with a previous user are inaccessible to current inhabitants.
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Glossary As known architectural words have implication, systemic expressions should probably be derived from the field of cybernetics and computer science. Measurable aspects of the systemic behaviour, can be also communicated verbally. The fact, that this project borrows from the terminology of computer science also helps in communicating, that the envisioned system is a computer. This radical approach towards terminology could furthermore verbalize the attitude to end the hegemony of modernism, and thus terminology is part of the concept. Terminology is also crucial considering the modes of verbally communicating the regulatory mechanisms from the side of the inhabitant.
Bb Belousov- Zhabotinsky (BZ) reaction 1
Tyson, J. J. “What everyone Should Know About the Belousov-Zhabotinsky
Reaction” Lecture Notes in Biomathematics 100, (1994) : 569
Homogenous oscillatory chemical reaction where “an organic substrate is oxidized by bromate ions in the presence of transition metal ion. The reaction is carried out in acidic solution. It is a simple chemical model of the osidation of organic molecules in living cells.” 1
Bistability / multistability
A reaction in steady-state condition, with reactants flowing into a reaction zone while products are flowing out of it. Under these conditions, the concentrations in the reaction zone may not change with time, although the reaction is not in a state of chemical equilibrium.
Black Box
Systems whose internal mechanisms are not fully open to inspection.
Cc Chemical Coupling 2
Irving R EpsteinA. PojmanJohn. “An Introduction to Nonlinear chemical
“In a chemically coupled system the subsystems are coupled through chemical reactions between their reactants, products, or intermediates.” 2
Dynamics.” New York: Oxford University Press, 1998: 260
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Dd Data
Information of chemical concentrations and changes in atmospheric conditions that compiled by the system over a given time according to its relevant function to form memory that initiates a gradual material adaptation.
Ee Equilibrium
A state in which a system has its energy distributed in the statistically most probably manner; a state of a system in which forces, influences, reactions etc., balance each other out so that there is no net change.
Chemical equilibrium
When a reaction and its reverse are proceeding at equal rates.
Excitability ( BZ reaction)
Consists of two important characteristics Threshold of excitation and refractory period. The threshold is the minimum perturbation that will cause the system to jump and instantaneously change its chemical concentration to far extremes.
Ff FKN (Field, Körös and Noyes) mechanism : 3
Irving R EpsteinA. PojmanJohn. “An Introduction to Nonlinear chemical
Dynamics.” New York: Oxford University Press, 1998.
FKN (Field, Körös and Noyes) mechanism
“The important fact is that Field, Körös, and Noyes were able to explain the qualitative behaviour of the BZ reaction using the same principles of chemical kinetics and thermodynamics that govern “ordinary” chemical reactions.” 3 The Oregonator is the simplified form of the FKN – that came about as the FKN was computationally too expensive- with twenty or so elementary steps and chemical species. The Oregonator only has 3 variable concentrations
Hh Hysteresis
Dependence of a system not only on its current environment but also on its past environment
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Glossary
Ii Isomorphism
“The word derives from the Greek iso, meaning “equal,” and morphosis, meaning “to form” or “to shape.”
Mm Memory
Data storage preserving a concentration profile for a purposeful period of time. Due to transient nature of the chemical machine however the system cannot access previous concentration profile that has already been processed
Mesoscopic ( scale)
Scale inbetween microscopic and macroscopic.
Machine ( cybernetics)
Machine is a system which is defined by the ability to express behaviour and transformation in form of states.
Oo Oregonator
It describes the oscillatory behaviour and pattern formation in the BZ reaction with only three variable species concentrations and five “ elementary steps”.
Oscillating reaction
A type of reaction in which the concentrations of the products and reactants change periodically, either with time or with position in the reacting medium. Thus, the concentration of a component may increase with time to a maximum, decrease to a minimum, then increase again and so on.( Do we need an image here?) continuing the oscillation over a period of time. They all occur under conditions far from chemical equilibrium and all involved autocatalysis (ie. A product of a reaction step acts as a catalyst for that step.). This autocatalysis drives the oscillation by a process of positive feedback.
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Pp Parameters
Information of chemical concentrations and changes in atmospheric conditions that compiled by the system over a given time according to its relevant function to form memory that initiates a gradual material adaptation.
Polymer
Substances that have macromolecules composed of many repeating units Homopolymer Diblock Copolymer Alternating Copolymer Random Copolymer
Polyscalar
Pertaining to several different scales despite singularity at macroscopic scale.
Processor / Array of Processors
Polyscalar arrangement of subprocessors
Perturbation
Influence from an external body / source / inhabitant
Rr Reaction Diffusion
Chemical systems where the reaction and diffusion of chemical species coexist under a non-equilibrium condition.
Reagent
A substance reacting with another substance
Refractory Period
A time interval in which cells or propagating waves are unresponsive, recovering from the previous stimulus and returning to its ‘excitable ‘ condition.( The refractory period occurs are result of the bromous acid being destroyed behind the wave front so again the wave stops because the reaction cannot immediately switch to production again.)
Ss Sub processor
The smallerst unit of processors that composes a physique of greater scale1
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06 MARS:SCENARIO/ PROTOTYPE_Why Mars? _Research/ Precedents _Fabrication _Deployment _Setup _Systemic Performance
06 MARS
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Scenario
Why Mars? There has already been numerous proposals for habitation on Mars, all with an ambition of re-creating an envrionment fit for human habitation and a temporary research facility. Fundamentally insular in intent, none aims to contribute to the greater environment of Mars or cultivate biological evolution on Mars. This attitude of building is a direct transportation of architectures that failed on Earth brought to Mars. It would be a lost opportunity not to suggest a new system of building and also a new mode of inhabitation. The purpose of our project is to demonstrate how a self-regulating system could lead to a mode of inhabitation and to the generation of spatial conditions In order to exploit the full potential of the chemical machine we have chosen mars as the testing ground. The project does not aim to recreate life on Earth , and endeavours to biosynthesise life on Mars in a non- humancentric way and to propagate it in order for them to later engage in their own evolution.
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Research/ LIfe support systems (NASA) Environmental control and life support system (NASA) A life is a system provides or controls atmospheric pressure, fire detection and suppression, oxygen levels, waste management and water supply.
Fig.1: Oxygen requirements
• Provides oxygen for metabolic consumption • Provides potable water for consumption, food preparation and hygiene uses • Removes carbon dioxide from the cabin air • Filters particulates and microorganisms from the cabin air • Removes volatile organic trace gases from the cabin air • Monitors and controls cabin air partial pressures of nitrogen, oxygen, carbon dioxide, methane, hydrogen and water vapor • Maintains total cabin pressure • Maintains cabin temperature and humidity levels • Distributes cabin air between connected modules The system aims to recreate earthlike modes of inhabitation.
Fig.2: Fundamental requirement for Mars Habitat
Fig.3: Human input and output AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Fig.4: Concept Ecological Control and Life Support System (NASA) 309
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Research/ Terraforming
Terraforming of Mars The terraforming of Mars is the hypothetical process by which the climate, surface and known properties of Mars would be deliberately changed with the goal of making it habitable by humans and other terrestrial life; and thus providing the possibility of safe and sustainable colonization of large areas of the planet.
Fig.5: An artist’s conception of terraforming AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Steps of terrafoming Phase 1 is warming Mars from the present cold state and restoring the thick atmosphere of CO 2. Phase 2 is the production of O 2 in sufficient quantities to be breathable by humans. WClimate calculations have shown that if there is CO 2 ice present in the polar regions of Mars, then a warming of 20 째C will cause the complete evaporation of that ice through a positive feedback mechanism. A self-regulative process without human intervention will start.
Fig.6: Three stages of terraforming process 311
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Precendents/ Habitation on Mars_Overview Volcanic Cave Settlement
Fig.7: Volcanic Cave Settlement
The Volcanic Cave Settlement concept is based upon the discovery of caves in the surface of Mars near an extinct volcano, Arsia Mons. The concept utilizes lava caves for shelter. Compared to other settlement types the cave settlement provides the biggest habitat space with respect to the transported construction material. The entrance to the cave is sealed with a pre-processed airlock. The preparation of a natural cave is simple and can be easily remote controlled. It offers the best protection against radiation and meteorites and is, therefore, considered to be part of the unmanned setup of a whole settlement. There may be dangers associated with creating a habitat in a cave, such as the cave collapsing due to ground quakes, poison gases that seep through the walls, and possible contamination of any native life. Fig.11: Volcanic Cave Settlement_ Space
Fig.8: Volcanic Cave Settlement_Construction
Multilayered Dome Settlement
Fig.9: Multilayered vaults
Fig.10: Multilayered vaults AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
A multi-layered vault settlement is a building, consisting of several shells. Each shell serves a different purpose: The central shell is the best protected part of the settlement, best useful for living rooms. The outermost shell contains store rooms, greenhouses, machinery, etc. It can be dome or barrel shaped. Rectangular column, beam and girder design with steal structural members as used on Earth would not be appropriate on Mars for any structure intended for human habitation. On Mars the first need for a habitation is that it be a pressure vessel to hold in enough air pressure for human survival, so cylindrical and spherical buildings would be built. One option is to dig a semicircular cross section ditch and build a cylindrical building in the ditch with its axis horizontal. Structural tension members would wrap around the entire building; roof, wall and floor to hold air pressure in. Tensile reinforcement would also run lengthwise through the outer wall from end to end. Another option for brick construction is to have a flat slab floor semi cylindrical roof structure and enough fill material over the roof so that the weight of the fill holds in the air pressure in the building below without the need for tensile strength in the walls of the structure. About 30 feet of brick and fill would be required to provide the necessary pressure. The inner
surface of the pressure vessel must be lined with gas a impermeable layer. Buildings would be made to their design size when first built. There would be no particular advantage to building a new layer of habitation above a previous building because the previous pressure vessel would be wasted and a new outer pressure retaining layer would be required. Bricks from sintered regolith allow the construction of vaults without any further material if the building is for unpressurized storage. Gravity alone stabilizes the building. Neither reinforcement nor grout is necessary. However, for people to inhabit a structure on Mars it needs to retain atmospheric pressure. A brick dome on Mars will require steel, fiberglass, or some other structural reinforcement strong in tension to hold in air pressure. It will be most economical to continue the tension members below ground level to form a fully spherical building with the hemispherical dome showing on top and the inverted dome section for a basement and sub basement.
Fig.12: Inflatable/ Dome
Domes/ Inflatables Inflatable structure, naturally asuming spherical shapes, can be used for permanent surface habitats or as a temporary base to be used during the building phase of e.g. brick vaults. Besides useful for habitation, inflatables are considered to be suitable for crop growth, as the greenhouse effect grants high temperatures. nflatable habitats offer the most benefit to initial settlements and outposts which require buildings shipped from Earth. They offer greater space than rigid habitats of the same initial volume.
Fig.13: Nasa Inflatable Habitat
Fig.14: ISS Habitat Module 313
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Precendents/ Habitation on Mars_ The Homestead Project Hillside Settlement: The Homestead Project (2025), by Mars Society
Fig.15: The Homestead Project
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Fig.17: Construction Method AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
The Hillside concept originates from the primary design of human settlement on the surface of Mars by the Mars Foundation. Known as the Mars Homestead Project™ this concept utilizes local materials where possible and proposes energy generation by nuclear power. The Hillside design maximizes protection from solar radiation, insulation from the extreme low temperatures and low Martian pressure. On analysis of possible settlement locations, Candor Chasma (part of the vast Valles Marineris canyon system) was selelected as an excellent candidate for the Hillside concept. The low tech construction method is based on Roman style vaults of bricks using native raw materials. It is intended to recreate the ancient history of mankind’s first settlements and to keep ancient architecture of compression. The brick vaults allow subterranean habitation using leaning arches and self supporting domes allowing the construction of a wide range of spaces using no scaffolding. However the majority of spaces has no views to the Mars surface. The Homesetad project is proposing an masonry structure, which is inherently not designed for a changing environment and thus unable to perform. It relies on resources, which may not be available on Mars. Looking at precedents on deployment, earth-like systems fit for human inhabitation and mostly temporary research are being proposed. Due to their intrinsic unsuitability for Mars, these systems are insular to the environment and do not aim to contribute to the greater Mars environment. Disparate building systems cannot perform in a constantly chemically and physically context of Mars. It would be a lost opportunity not to suggest a new system of building and also a new mode of inhabitation. The purpose of our project is to demonstrate how a self-regulating system could lead to a mode of inhabitation and to  the generation of spatial conditions
Fig.18: Lower Level Plan
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Precendents/ Habitation on Mars_ The Homestead Project
Fig.19: Lower Level Plan/ Core Settlement Fig.20: Section AA/BB
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Fig.21: Power, ECLSS, and Manufacturing
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Research | Precedents | Conditions
Size Mars has approximately half the diameter and 15% volume of Earth.
Fig.23: Size comparison for Earth and Mars
Geology Mars is a terrestrial planet that consists of minerals containing silicates (silicon and oxygen), metals, and other elements that typically make up rock. Much of the surface is deeply covered by finely grained iron oxide dust.
Fig.24: Air, mineral and soil compositions on Mars AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Hydrology
Atmosphere (Pressure/Composition)
Liquid water almost cannot exist on the surface of Mars due to low atmospheric pressure. The two polar ice caps appear to be made largely of water. The volume of water ice in the south polar ice cap, if melted, would be sufficient to cover the entire planetary surface to a depth of 11 meters.
The mean pressure at the surface level of 600 Pa (0.60 kPa).The resulting maximum surface pressure is only 0.6% of that of the Earth (101.3 kPa).
Fig.27: Pressure comparison between Earth and Mars
Fig.25: Environmental conditions
Mars have subsurface water ice on Mars.
The atmosphere of Mars consists of about 95% carbon dioxide, 3% nitrogen, 1.6% argon and contains traces of oxygen and water. The atmosphere is quite dusty.
Fig.26: Environmental conditions
Fig.28: Atmospheric gas 319
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Climate(Season/Temperature/Dust Storm)
During the Martian summer in the Northern Martian hemisphere, Mars has the largest dust storms in the Solar System.
The seasons of Mars are the most Earth-like but lengths of the Martian seasons are about twice.
Fig.31: Dust strom on Mars
Radiation Fig.29: Martian seasons
Martian surface average temperatures is around -60 °C. The wide range in temperatures is due to the thin atmosphere which cannot store much solar heat, the low atmospheric pressure, and the low thermal inertia of Martian soil. The planet is also 1.52 times as far from the Sun as Earth, resulting in just 43% of the amount of sunlight.
Fig.30: Temperature on Earth and Mars AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
A significant amount of ionizing radiation to reach the Martian surface. Average doses were about 22 milliards per day, A three-year exposure to such levels would be close to the safety limits.
Geomagnetic field Mars has no global magnetic field comparable to Earth’s geomagnetic field. Its magnetic fields are “fossil” remnants of its ancient, global magnetic field.
Fig.32: Earth and Martian Magnetic Fields
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Research | Precedents | The Gale Crater | Curiosity
Gale Crater One of the typical landing site selection is Gale Crater, which is near the north-western part of the Aeolis quadrangle at 5.4째S 137.8째 on Mars. It is 154 km (96 mi) in diameter and estimated to be about 3.5-3.8 billion years old. It was selected by NASA as the landing site for Curiosity rover in 2012. We plan to land our chemical machine at the foot of a layered mountain within this massive crater. The portion of the crater where the machine would land might be ancient waterfront on Mars through analysis of the soil composition by Curiosity.
Gale Crater
Fig.33: Topography of Mars
Fig.34: Topography of Gale crater
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Curiosity The Curiosity rover is a car-sized robotic rover exploring Gale Crater on Mars as part of NASA’s Mars Science Laboratory mission (MSL). With the help of the investigation of the Martian climate and geology, we can get relatively specific and precise data of the site where we plan to land the chemical machine. In addition, the Curiosity also would participate the hydration and pressurization process after landing on Mars.
Fig.35: Curiosity rover
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Timeline
2012 Robitic exploration starts in 2012.
2022 Release of supergreenhouse gases starts in 2022 as an initial part of terraforming process. In this stage the main aim is to release the Carbon dioxide below the surface of Mars to warm and thicken the atmosphere and to melt the ice on the surface. By 200 years rain could form and waterways are projected to be created. Bacteria and algae would thrive in the warmed up climate. There would be an increase in the amount of Oxygen and nitrogen in the atmosphere. The atmospheric oxygen levels would reach beyond 20 megabar which allows for the growth of flowering plants. They will further increase the atmospheric oxygen levels to 60 megabar.
2032 After the initial phase of robotic exploration and the gradual environmental change due to the release of supergreenhousegases, the processor and microorganisms will be deployed on 5 different locations which are close to potential water bodies on Mars. For the prototype, the chosen site is around the Gale Crater, which is currently being analysed by the Curiousity Rover.
2035 The initial setup process will be completed by the arrival of people approximately two years after the initial deployment in 2035.
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2040 The further process of colonization is conducted by the chemical machine leaving seeds on the Martian ground as well as by the propagation of earth originated biological life. Seeding is a result of the chemical machine‘s time based and self- led development while it responds to its environment and inhabitants in constant flux.  Whole system is a computing superorganism and ecosystem composed of chemically interrelated processors which is the chemical machine at its maximum scale. The growing processs evolves and engages with a biological and synthetic evolutionary process. AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
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The proposal | On earth fabrication
Deployment The spaceship will transport the processors in their dehydrated state and chemically concentrated state, as well as the biologically active matter besides the. Upon arrival, the chemical machine are hydrated and inflated by robotic construction methodologies.
Earth
Atlas V-541
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Journey
Setting up: Hydration/ Inflation
On Earth fabrication The fabrication process happening on Earth includes 3 steps: firstly, we hydrate the hydrogels by immersing them into the BZ reaction liquid reagent. After hydrogels absorb sufficient reagent, we start to dehydrate them to quite small size and put them into the membrane. Finally, we try to use folding and vacuuming operations to make them compact and also as a space strategy.
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3mm dia dehydrated
20mm dia hydrated
Fig.36: Hydrating test 329
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The proposal | On earth fabrication
Digital simulations for dehydration and vacuumization
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The proposal | Inflation Research
Basic geometry tests
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The proposal | Inflation Research
Inflating section simulations
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The proposal | Inflation Research
Folding geometry I
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The proposal | Inflation Research
Test 2
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Test 4
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The proposal | Inflation Research
Folding geometry II
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Test 2
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The proposal | The journey: Atlas
Prototype
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Atlas V-571 Atlas is a family of United States space launch vehicles. Atlas v-541 will transport the processors in their dehydrated and chemically concentrated state, as well as the photosynthetic biologically active matter such as Algae and cyanobacteria.
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The proposal | hydration and inflation on Mars
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Physical simulation
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The proposal | hydration and inflation on Mars
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Setup/ Design Criteria & Programme
Design Critiera Chemical Machine (Prototypical) 1) Maximum Neighbours: Building component scale (subprocessor) and spatial scale Implications: Compactness in overall structure and clustering of (cellular) spaces 2) Geometry: Spherical geometries are more beneficial for sustaining the propagating wave 3) Matter distribution: Strategic distribution of computing sub-processors in consideration to envisioned systemic performance
Design Critiera Mars (Scenario-based) Physical Design 1) Compactness: Efficient surface/ volume ratio due to Martian cold climate 2) Pressurized structure capable of adapting to changing Martian air pressure Implications: Tensile membrane enabling adaption to changing Mars environment as well as to temporary morphological self-regulative results 3) Matter distribution: Exterior compartment of the processor wall needs more material due to a higher envisioned performative necessity
Programmatic requirements -habitation units for 27 people -circulation -Farm -Air lock
AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Exploration Ratio 1 Dimensions (diameter, if applicable) : 11,2 / 8 m Volume (outer and inner) : 730 m³ / 264 m³ Thickness of envelope: 1,6 m / 80 subprocessors Ratio mass and volume: 2/3 and 1/3 exterior surface area / interior surface area: 392.4 m² / 200 m²
Exploration Ratio 2
Dimensions (diameter, if applicable) : 12,24/ 9,714 m Volume (outer and inner) : 958 m³ / 479 m³ Thickness of envelope: 1,263 m / 63 subprocessors Ratio mass and volume: 1/2 and 1/2 exterior surface area / interior surface area: 470 m²/ 296 m²
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Design Process/ Exploration Clusters/ Organization
Farm
Units
Ratio 4
Dimensions (diameter, if applicable) : 14,01/ 9,714 m Volume (outer and inner) : 1914,5 m³ / 1437,5 m³ Thickness of envelope: 0,702 m / 35 subprocessors Ratio mass and volume: 1/4 and 3/4 exterior surface area / interior surface area: 745.8 m² / 616 m²
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Ratio 6
Dimensions (diameter, if applicable) : 16,6 / 15,4 m Volume (outer and inner) : 2400 m³ / 1920 m³ Thickness of envelope: 0,606 m / 30 subprocessors Ratio mass and volume: 1/5 and 4/5 exterior surface area / interior surface area: 866 m² / 746 m²
Units
Farm
Farm Farm Farm
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Design Process/ Exploration Clusters/ Organization
Cluster catalogue_centrally accessed Units
Farm
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Cluster catalogue_decentrally accessed
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Setup/ Clusters
Basic cluster 2 inhabitants 1 farm
6 inhabitants 3 farms
8 inhabitants 4 farms
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4 inhabitants 2 farms
Considering the previously defined design criteria of maximum neighbors on building component as well as spatial scale, a clustering of spatial units is A natural result. Clustering allows a more efficient volume to surface ratio of the overall global structure.
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Setup/ Clusters
Fig.37: Setup before fixing
Fig. 38: Deformed cells due to physical implications (Clematis vitalba) AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Pullpoint
Pullpoint
Airlock Farms Inhabitation
Airlock
Pullpoint Fig.39: Physical deformation of setup by fixing and inflation 363
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Setup/ Life support system
Macroenvironment Oxygen: 30 kg/pd Food Waste: 60 kg/pd CO2: 30 kg/pd
Biological Algae, Lich Cyanobacte
Microenvironment 30 People Humidity: 60 kg/pd Heat: 60 kW/pd
Light
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CO2
Heat Substrate Water 10000 lux light
Life: hen eria
Oxygen
Processor
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Setup/ Section
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Setup/ Cluster Section
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Setup/ Organizational logic
Exterior Tensile Membrane CO2 Sensing pores/ Perturbation points Embedded biological vessels with Oxygen emitting pores
Sub-processors Macroenvironment
Internal Tensile Airtight Membrane
Sub-processors Microenvironment
Interior Tensile Membrane
Homogenous distribution of pores for sensing Embedded biological vessels with emitting pores
Pressurized Volume
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Setup/ Quantified Design
Quantification: Performative Capacity The systemic design is based on the intended performance in regards to environment and inhabiting chemical agencies. The machine is capable of releasing a volume of oxygen equalling its own volume. In order to maintain photosynthesis in the absence of natural light, the machine offers 10000 lux constantly. Compared to the environmental affect, the performance for the inhabiting microorganisms and people is minor. Considering the performative need of the system, we need to strategically accumulate a larger share of subprocessor material in the exterior part of the wall. The interior spatial structure follows the performative needs of the system of the inhabitants.
Macroenvironmental performance Co2/ Light: 12430800 computing sub-processors (99%)
Microenvironment: 30 People:
-30 kg Co2/ 24 h and 30 kg O2 / 24 h => 21 g of gas exchange/ min by internal surface pores
Macroenvironment: Microorganisms:
Productivity Cyanobacteria: -0.35 mmol/l = 6.3 mg/dl OR 0,063g/ m³ in one hour per gram bacteria Required productivity: -The Chemical Machine affects a Macroenvironment of 480 m³ in terms of gas exchange, which equals it own solid mass (480 m³ * 1,977 kg/ m³) *95%=> 901 kg => 901000 g per day OR 37542 g per hour Required amount of cyanobacteria: 37542 g/ 0,063g/ m³ => 595904 g per 480 m³ OR 1241 g/ m³ -each bacteria vessel has a diameter of 10 mm and can house 10 g of bacteria, each m³ of the processor needs 124 bacteria vessels
Exterior Surface Pores:
-Minimum surface area processor => 400 m² -Oxygen release per hour => 37542 g 37542 g/ 400 m² => 93,855 g/ m² Assumption: 100 pores per 1 m² (in case of minimum surface area)
Light:
-each 20 mm subpr. can emit 2 lux/min -a constant supply of 10000 lux is necessary to grant photosynthesis => 26000 subpr/ min (incl. 1/3 Refractory State)
Total:
Total: 12500000 subprocessors / 525 m³ (including membrane) Dehydrated (earth): 1000 kg (matching weight constraints)
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Microenvironmental performance Co2 (Inhabitants): 43200 computing sub-processors
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Setup/ Interior Detail
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Subprocessors
CPU Allow morphological and environmental selfregulation by mechanical oscillation and emission of light
Biological Vessels
Regulate the oxygen level of the microenvironment
Interior Membrane with Pores -Allows sensing of carbondioxide -allows moisture exchange with microenvironment
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Setup/ Exterior Membrane
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Setup/ Interior Membrane
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self-regulation
Merit in self-regulating architecture on Mars Mars is an extreme scenario chosen to fully exploit the maximum potential of the self –regulatory feature of the hypercells. Unless hypercells are situated in such context the dire need and the importance of self-regulation cannot be tested also. Self-regulation is part of the survival process of the micro-ecology which hypercell harbours which also included human settlement. The self-regulation is orchestrated by the hypercells, however they are perpetuated by several factors. 1. The existing environmental conditions of mars 2. Inhabitors /human engagement within the hypercells micro-ecology 3. Biological input through photosynthesis
MACROCLIMATE of MARS Light Processes Physical Manipulation as information
Biological Life
Fig.40: Astroculture AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Oxygen
Processes CO2 as information
Oxygen
Oxygen CO2 communicated as pH
Light
Oxygen CO2
Physical Manipulation
MICROCLIMATE of MARS Individual
For regulation of an environment no only fit for human survival, but for many other living beings the presence of plants are cruicial. It too is a self- regulatory aspect of the proposal which also significantly simplifies the chemical regulation procedure of the microclimate created by Hypercells on Mars.
Visual and spacial information **
Membrane
Processor
Processes Physical Manipulation as information
Membrane
Processes pH as information Processes Light as information
Processes sensory information
Visual and spacial information **
CO2 communicated as pH
Light (chemical trigger)
This possible changes to the spatial organisation due to physical swelling and deswelling, as well as light, and possibly other sensory experiences which the human could register. Physical Defomation as a productive source deformation - that governs the pore opening and closing as a result of computation Take Biological life and its processes of photosynthesis as given as it is NOT part of what we are designing.
Plants gowing on the International Space Station Fig.41: < The ASTROCULTURE™ is the first facility to grow plants that produce seeds on the International Space Station. Technology for this facility is based on the ASTROCULTURE™ plant growth unit, flown six times on NASA’s Space Shuttle and once on the Russian Mir space station.
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Chemical Processsing/ Physical Movement
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Digital Animations // based on bz code The thichness of the initial setups, affect the route and latency of the wave propagation within the designed configurations. While the thiner sections are easy to be triggered and direct the wave propagation in a faster way , on the thicker sections, the wave is more propagation is more stable and delayed. This principle is used for handling the light distribution according to the need of light level of the users. The arrengement of units that will be inhabited by a person creates a neigbourhood rule which affects the design desicion while distrubuting the initial space. Whereas hexagonal packing allows the wave propagation in as many as six directions and allows the communication with maximum number of neighbour inhabitable units, square and triangular formation of the units limits the performance based on the trasmitting the chemical wave.
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In the detailed scale of the prorotype, the initial geometry of the adaptive membrane which is housing the subprocessors gives the ability of self regulation to the system regarding to processed information over time. The variation of the articulated membrane affects the systemâ&#x20AC;&#x2122;s long term behaviour and perform unexpected results. Due to the composition of expansion and shrinkage forces of the subprocessors and the initially given geometry and flexibility of the membrane, temporary spaces occur.
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While the inhabitable space shapes up its spatial configuration, curved surfaces such as concave and convex formations bust the behaviour of adaptibility to the environment and programmatic flexibility.
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Chemical machines ability of sensing the physical inputs, adaptibility to its environment and the self regulation capabilities define the mode of operation and inhabitation consequently.
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In the mars based scenario, this approach has been materialised by chemical interaction and communication rules between subprocessors which challanges the functionality of the smallest building element in the current architecture.
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Bibliography/ Image Credits
Bibliography Cohen, Marc M. “The Five Showstoppers for Mars Habitation.” Astrotecture. (2011). http://spaceconf.com/papers/marccohenpaper.pdf (accessed October 27, 2012). Fogg, M.J. “Terraforming Mars:A Review of current research.” Avdanced Space Research. Volume 22. no. 3 (1998): 415-420. Graham, JAMES. “The Biological Terraforming of Mars: Planetary Ecosynthesis as Ecological Succession on a Global Scale.” ASTROBIOLOGY . Volume 4. no. 2 (2004): 168-195. Hoffman, Stephen J., and David I. Kaplan. “Human Exploration of Mars:The Reference Mission of the NASA Mars Exploration.” NASA Special Publication 6107. (1997). http://ares.jsc.nasa.gov/HumanExplore/Exploration/EXLibrary/docs/MarsRef/contents.htm (accessed January 29, 2013). “International Space Station Environmental Control and Life Support System.” Nasa Facts. . http://www.nasa.gov/centers/marshall/pdf/104840main_ eclss.pdf (accessed October 27, 2012). Jairala, Juniper. “Design of a Martian Habitat, a First Cut.” . http://www.uss-hornet.org/groups/pdf/SEMB_MarsHabitat.pdf (accessed October 27, 2012). McKay, Christopher P. “Flowers for Mars.” The Planetary Report. (2000): 4-5. McKay, Christopher P. “Biologically Reversible Exploration.” Science. VOL 323. (6 FEBRUARY 2009): 4-5. McKay, Christopher P. “Astrobiology and Society: The long view.” (2009). McKay, Christopher P. “Planetary Ecosynthesis on Mars and Geo-Engineering on Earth: CanWe? Should We? Will We?.” Engineering Earth. (2011): 2227-2232. McKay, Christopher P., and MARGARITA M. MARINOVA. “The Physics, Biology, and Environmental Ethics of Making Mars Habitable.” ASTROBIOLOGY. Volume 1. no. 1 (2001): 89-110. McKay, Christopher P. Exploring the Origin, Extent, and Future of Life: Philosophical, Ethical, and Theological Perspectives. Cambridge: Cambridge University Press, 2009. McKay, Christopher P., Thomas R. Meyer, and Penelope Boston. “Utilizing Martian Resources for Life Supprt .” Resources of Near-Earth Space. : 819843. http://www.uapress.arizona.edu/onlinebks/ResourcesNearEarthSpace/resources29.pdf (accessed November 10,2012). Petrov, Georgi I., Bruce Mackenzie, Mark Homnick, and Joseph Palaia. “A permanent settlement on Mars: The architecture of the Mars Homestead Project.” Mars Home. (2005). Rapp, Donald. “MARS LIFE SUPPORT SYSTEMS.” The Mars Journal. Volume 2. (2006): 72-82. http://www.marsjournal.org/contents/2006/0005/ (accessed October 27, 2012). Sabouni, Dr. Ikhlas , Roy Smith, and Steven Taylor. “DESIGN AND DEVELOPMENT OF THE SECOND GENERATION MARS HABITAT.” PrairieView A&M University. (1992): 228-236. http://ntrs.nasa.gov/search.jsp?R=19940021200 (accessed October 27, 2012). AA Design Research Laboratory 2013 - TEAM:SPORES - hypercells
Sabouni, Dr. Ikhlas . “MARS HABITAT.” DEPARTMENT OF ARCHITECTURE COLLEGE OF ENGINEERING & ARCHITECTURE PRAIRIE VIEW A&M UNIVERSITY. (1991). http://www.spacearchitect.org/pubs/NASA-CR-189985.pdf (accessed October 27, 2012). Zubrin, Robert, and Richard Wagner. The case for Mars: the plan to settle the red planet and why we must. New York: Free Press, 1996.
Image Credits Fig.1-2: Rapp, Donald. “MARS LIFE SUPPORT SYSTEMS.” The Mars Journal. Volume 2. (2006): 72-82. http://www.marsjournal.org/ contents/2006/0005/ (accessed October 27, 2012). page 9, page 11. Fig.3: Jairala, Juniper. “Design of a Martian Habitat, a First Cut.” . http://www.uss-hornet.org/groups/pdf/SEMB_MarsHabitat.pdf (accessed October 27, 2012). p.9 Fig.4: Concept Ecological Control and Life Support System (NASA) Jairala, Juniper. “Design of a Martian Habitat, a First Cut.” . http://www.uss-hornet.org/groups/pdf/SEMB_MarsHabitat.pdf (accessed October 27, 2012). p.10 Fig.5: http://www.bizarrebytes.com/the-energy-of-terraforming/terraforming/ Fig.6: http://www.drg-gss.org/typo3/html/index.php?id=74 Fig.7-9: http://www.marspedia.org/index.php?title=Volcanic_cave_settlement Fig.10-11: http://www.marspedia.org/index.php?title=Multi-layered_vault_settlement Fig.12: Zubrin, Robert, and Richard Wagner. The case for Mars: the plan to settle the red planet and why we must. New York: Free Press, 1996. page 170 Fig.13: http://www.nasa.gov/exploration/home/inflatable-lunar-hab.html] http://fabricarchitecturemag.com/posts/buyersguide/615 Fig.14: http://fabricarchitecturemag.com/posts/buyersguide/615] Fig.15: http://www.marspedia.org/index.php?title=Hillside_settlementt Fig.16: Petrov, Georgi I., Bruce Mackenzie, Mark Homnick, and Joseph Palaia. “A permanent settletment on Mars: The architecture of the Mars Homestead Project.” Mars Home. (2005). Fig.17-21: Petrov, Georgi I., Bruce Mackenzie, Mark Homnick, and Joseph Palaia. “A permanent settlement on Mars: The architecture of the Mars Homestead Project.” Mars Home. (2005). oage 10, 37, 38, 40, 41,42 Fig.22: Zubrin, Robert, and Richard Wagner. The case for Mars: the plan to settle the red planet and why we must. New York: Free Press, 1996. page 171 Fig.26: http://mars.jpl.nasa.gov/express/spotlight/20050504.html Fig.27-28: http://resources.yesican-science.ca/trek/mars2/final2/mars_info/mars_info_climate.html Fig.29: http://www.britannica.com/EBchecked/media/70791/The-seasons-of-Mars-a-result-of-the-planets-inclination Fig.30: http://resources.yesican-science.ca/trek/mars2/final2/mars_info/mars_info_climate.html Fig.31: http://www.haveeru.com.mv/mars Fig.32: http://www.nasa.gov/mission_pages/msl/multimedia/hassler02.html Fig.33: http://marsrover.nasa.gov/gallery/landingsites/ Fig.34: http://en.wikipedia.org/wiki/Gale_(crater) Fig.35: http://www.zmescience.com/space/curiosity-drill-malfunction-jeopardize-entire-mission-424343/ Fig.38: http://www.mikroskopie-forum.de/index.php?topic=9121.0 Fig.40: http://www.lightpublic.com/lighting-articles/forbes-farming-the-moons-lava-tubes-with-leds/] Fig.41: http://www.nasa.gov/audience/foreducators/plant-growth-gallery-index.html] 397
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Thanks to Theodore Spyropoulos Ryan Dillon Robert Stuart-Smith Professor Andrew Adamatzky Jeff Jones International Center of Unconventional Computing, Bristol, UK Dr. Tetsuya Asai Graduate School of Information Science and Technology, Hokkaido University Dr. Yukio- Pegio Gunji Nonlinear Science Laboratory Graduate School of Science, Kobe University, Japan Roman Kirschner Media Artist, Germany Theresa Schubert Ph.D. candidate in Fine Art / Bauhaus-Universit채t Weimar Research & Project Management / Ars Electronica Archive Prof. Dr. Wolfgang Marwan Max-Planck-Institut f체r Dynamik komplexer technischer Systeme, Germany Dr. Chris McKay Space Science and astrobiology at Ames NASA Irene Chen Krystyn j. Van Vliet, ph.D Massachusetts Insitute of Technology Prof. Dr. Carsten Werner Head of Institute Biofunctional Polymer Materials Dr.Stefan Gramm Dr. Mirko Nitschke Leibniz-Insitut f체r Polymerforschung Dresden e.V. Irem Dokmeci Sakshi Mathur Haris Mashkoor Steven Haocheng Yang Yekta Ipek Anja Karlstaedt Eleni Meladaki